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- 【影视】 [FreeCoursesOnline.Me] [Packtpub.Com] Building Machine Learning Systems with TensorFlow - [FCO]
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收录时间:2022-02-10
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Chapter 7 - Recurrent Neural Networks and LSTM/35. Writing Music a la Bach.mp4 47.1 MB
Chapter 1 - Exploring and Transforming data/04. Basic Tensor Methods.mp4 38.7 MB
Chapter 4 - Logistic Regression/18. Univariate Logistic Regression.mp4 33.2 MB
Chapter 1 - Exploring and Transforming data/02. TensorFlow's Main Data Structure Tensors.mp4 28.5 MB
Chapter 3 - Linear Regression/14. Univariate Linear Regression.mp4 26.5 MB
Chapter 1 - Exploring and Transforming data/05. How TensorBoard Works.mp4 25.8 MB
Chapter 1 - Exploring and Transforming data/06. Reading Information from Disk.mp4 22.9 MB
Chapter 3 - Linear Regression/15. Multivariate Linear Regression.mp4 22.6 MB
Chapter 2 - Clustering/10. Project 1 k-Means Clustering on Synthetic Datasetsets.mp4 20.4 MB
Chapter 2 - Clustering/09. k-Nearest Neighbor.mp4 19.8 MB
Chapter 1 - Exploring and Transforming data/01. The Course Overview.mp4 19.5 MB
Chapter 6 - Convolutional Neural Networks/25. Applying Convolution in TensorFlow.mp4 18.8 MB
Chapter 6 - Convolutional Neural Networks/29. MNIST Digit Classification.mp4 18.7 MB
Chapter 1 - Exploring and Transforming data/03. Handling the Computing Workflow TensorFlow's Data Flow Graph.mp4 17.0 MB
Chapter 5 - Simple FeedForward Neural Networks/22. Second Project Modeling Cars Fuel Efficiency with Non-Linear.mp4 16.4 MB
Chapter 8 - Deep Neural Networks/40. Painting with Style VGG Style Transfer.mp4 16.2 MB
Chapter 7 - Recurrent Neural Networks and LSTM/34. Univariate Time Series Prediction with Energy Consumption Data.mp4 14.5 MB
Chapter 9 - Library Installation And Additional Tips/42. mac OS Installation.mp4 14.3 MB
Chapter 5 - Simple FeedForward Neural Networks/21. First Project Non-Linear Synthetic Function Regression.mp4 14.3 MB
Chapter 5 - Simple FeedForward Neural Networks/20. Preliminary Concepts.mp4 14.0 MB
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- 【影视】 Complete Tensorflow 2 and Keras Deep Learning Bootcamp
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[TutsNode.net] - Complete Tensorflow 2 and Keras Deep Learning Bootcamp/9 - Recurrent Neural Networks RNNs/89 - Bonus Multivariate Time Series RNN and LSTMs.mp4 246.5 MB
[TutsNode.net] - Complete Tensorflow 2 and Keras Deep Learning Bootcamp/1 - Course Overview Installs and Setup/3 - Course Setup and Installation.mp4 242.8 MB
[TutsNode.net] - Complete Tensorflow 2 and Keras Deep Learning Bootcamp/9 - Recurrent Neural Networks RNNs/88 - RNN Exercise Solutions.mp4 240.8 MB
[TutsNode.net] - Complete Tensorflow 2 and Keras Deep Learning Bootcamp/7 - Basic Artificial Neural Networks ANNs/58 - Tensorboard.mp4 236.0 MB
[TutsNode.net] - Complete Tensorflow 2 and Keras Deep Learning Bootcamp/7 - Basic Artificial Neural Networks ANNs/51 - Keras Project Solutions Exploratory Data Analysis.mp4 230.7 MB
[TutsNode.net] - Complete Tensorflow 2 and Keras Deep Learning Bootcamp/13 - Deployment/116 - Live Deployment to the Web.mp4 204.9 MB
[TutsNode.net] - Complete Tensorflow 2 and Keras Deep Learning Bootcamp/9 - Recurrent Neural Networks RNNs/86 - RNN on a Time Series Part Two.mp4 204.9 MB
[TutsNode.net] - Complete Tensorflow 2 and Keras Deep Learning Bootcamp/7 - Basic Artificial Neural Networks ANNs/43 - Keras Regression Code Along Exploratory Data Analysis.mp4 200.3 MB
[TutsNode.net] - Complete Tensorflow 2 and Keras Deep Learning Bootcamp/12 - Generative Adversarial Networks/107 - Creating a GAN Part Three Model Training.mp4 181.3 MB
[TutsNode.net] - Complete Tensorflow 2 and Keras Deep Learning Bootcamp/7 - Basic Artificial Neural Networks ANNs/48 - Keras Classification Dealing with Overfitting and Evaluation.mp4 179.4 MB
[TutsNode.net] - Complete Tensorflow 2 and Keras Deep Learning Bootcamp/13 - Deployment/115 - Flask Front End.mp4 175.6 MB
[TutsNode.net] - Complete Tensorflow 2 and Keras Deep Learning Bootcamp/11 - AutoEncoders/99 - Autoencoder for Dimensionality Reduction.mp4 175.4 MB
[TutsNode.net] - Complete Tensorflow 2 and Keras Deep Learning Bootcamp/4 - Pandas Crash Course/18 - Data Input and Output.mp4 159.1 MB
[TutsNode.net] - Complete Tensorflow 2 and Keras Deep Learning Bootcamp/8 - Convolutional Neural Networks CNNs/72 - CNN on Real Image Files Part Three Creating the Model.mp4 141.9 MB
[TutsNode.net] - Complete Tensorflow 2 and Keras Deep Learning Bootcamp/7 - Basic Artificial Neural Networks ANNs/52 - Keras Project Solutions Dealing with Missing Data.mp4 139.8 MB
[TutsNode.net] - Complete Tensorflow 2 and Keras Deep Learning Bootcamp/7 - Basic Artificial Neural Networks ANNs/41 - Keras Syntax Basics Part Two Creating and Training the Model.mp4 131.0 MB
[TutsNode.net] - Complete Tensorflow 2 and Keras Deep Learning Bootcamp/13 - Deployment/110 - Creating the Model.mp4 128.0 MB
[TutsNode.net] - Complete Tensorflow 2 and Keras Deep Learning Bootcamp/5 - Visualization Crash Course/23 - Seaborn Basics.mp4 125.8 MB
[TutsNode.net] - Complete Tensorflow 2 and Keras Deep Learning Bootcamp/7 - Basic Artificial Neural Networks ANNs/53 - Keras Project Solutions Dealing with Missing Data Part Two.mp4 124.3 MB
[TutsNode.net] - Complete Tensorflow 2 and Keras Deep Learning Bootcamp/8 - Convolutional Neural Networks CNNs/71 - CNN on Real Image Files Part Two Data Processing.mp4 123.9 MB
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- 【影视】 Detecting Data Anomalies using Deep Learning Techniques with TensorFlow (Andrei Pruteanu, 2021)
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5. Detection Algorithms/3. Demo - Deep-Learning Approaches Part 1.mp4 29.7 MB
5. Detection Algorithms/4. Demo - Deep-Learning Approaches Part 2.mp4 26.4 MB
6. Mitigation Techniques/1. Techniques and Metrics.mp4 17.3 MB
5. Detection Algorithms/1. Demo - Statistical Approaches Part 1.mp4 16.8 MB
4. Definition and Anomaly Types/1. Taxonomy.mp4 14.8 MB
4. Definition and Anomaly Types/2. Real Data.mp4 13.5 MB
5. Detection Algorithms/2. Demo - Statistical Approaches Part 2.mp4 12.8 MB
3. Exploratory Data Analysis/3. Demo - EDA Part 2.mp4 11.6 MB
2. Introduction/2. Summary.mp4 8.9 MB
3. Exploratory Data Analysis/2. Demo - EDA Part 1.mp4 8.6 MB
2. Introduction/3. Statistical Methods.mp4 7.3 MB
3. Exploratory Data Analysis/1. Finding a Dataset.mp4 4.4 MB
1. Course Overview/1. Course Overview.mp4 4.0 MB
2. Introduction/4. Prerequisites.mp4 3.9 MB
2. Introduction/1. Introduction.mp4 3.4 MB
exercise.7z 1.9 MB
5. Detection Algorithms/3. Demo - Deep-Learning Approaches Part 1.vtt 14.0 kB
5. Detection Algorithms/4. Demo - Deep-Learning Approaches Part 2.vtt 13.8 kB
6. Mitigation Techniques/1. Techniques and Metrics.vtt 11.2 kB
5. Detection Algorithms/1. Demo - Statistical Approaches Part 1.vtt 8.9 kB
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- 【影视】 GetFreeCourses.Co-Udemy-TensorFlow 2.0 Practical Advanced
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收录时间:2022-04-22
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磁力链接
01 - INTRODUCTION AND COURSE OUTLINE/007 Whats New in TensorFlow 2.0.mp4 229.6 MB
05 - DEEP DREAM/008 Deep Dream Coding P5.mp4 221.2 MB
05 - DEEP DREAM/001 What is Deep Dream.mp4 203.4 MB
05 - DEEP DREAM/002 How does DeepDream Algo work.mp4 162.6 MB
02 - REVIEW OF ARTIFICIAL NEURAL NETWORKS AND CONVOLUTIONAL NEURAL NETWORKS/001 ANN and CNN - Part 1.mp4 149.3 MB
04 - AUTOENCODERS/013 Autoencoders Project 2 - Coding P2.mp4 147.5 MB
04 - AUTOENCODERS/001 Autoencoders intuition.mp4 124.4 MB
04 - AUTOENCODERS/20087012-traffic-signs-data.zip 121.4 MB
03 - TRANSFER LEARNING (TF HUB)/006 Transfer Learning Project 1 - Coding P2.mp4 114.9 MB
02 - REVIEW OF ARTIFICIAL NEURAL NETWORKS AND CONVOLUTIONAL NEURAL NETWORKS/010 Project 1 - Solution Part 2.mp4 106.3 MB
06 - GANs/010 GANS Project 1 P5.mp4 102.1 MB
08 - TENSORFLOW SERVING AND TENSORBOARD/003 TF Serving Coding Part 3.mp4 102.1 MB
05 - DEEP DREAM/007 Deep Dream Coding P4.mp4 101.9 MB
02 - REVIEW OF ARTIFICIAL NEURAL NETWORKS AND CONVOLUTIONAL NEURAL NETWORKS/007 ANN and CNN - Part 7.mp4 100.3 MB
07 - RECURRENT NEURAL NETWORKS (RNNs) AND LSTMs/006 Vanishing Gradient Problem.mp4 100.3 MB
07 - RECURRENT NEURAL NETWORKS (RNNs) AND LSTMs/007 Long Short Term Memory LSTM.mp4 96.7 MB
01 - INTRODUCTION AND COURSE OUTLINE/004 ML, AI and DL.mp4 96.2 MB
06 - GANs/001 GANS intuition.mp4 95.4 MB
03 - TRANSFER LEARNING (TF HUB)/005 Transfer Learning Project 1 - Coding P1.mp4 93.8 MB
03 - TRANSFER LEARNING (TF HUB)/007 Transfer Learning Project 1 - Coding P3.mp4 92.6 MB
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- 【影视】 GetFreeCourses.Co-Udemy-TensorFlow Developer Certificate in 2021 Zero to Mastery
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7. Transfer Learning in TensorFlow Part 2 Fine tuning/18. Preparing Model 3 (our first fine-tuned model).mp4 207.9 MB
3. Neural network regression with TensorFlow/11. Evaluating a TensorFlow model part 3 (getting a model summary).mp4 202.2 MB
5. Computer Vision and Convolutional Neural Networks in TensorFlow/15. Breaking our CNN model down part 5 Looking inside a Conv2D layer.mp4 195.1 MB
3. Neural network regression with TensorFlow/5. The major steps in modelling with TensorFlow.mp4 190.6 MB
7. Transfer Learning in TensorFlow Part 2 Fine tuning/3. Downloading and turning our images into a TensorFlow BatchDataset.mp4 182.0 MB
8. Transfer Learning with TensorFlow Part 3 Scaling Up/18. Making predictions on our test images and evaluating them.mp4 180.0 MB
4. Neural network classification in TensorFlow/9. Creating a function to view our model's not so good predictions.mp4 168.3 MB
7. Transfer Learning in TensorFlow Part 2 Fine tuning/14. Building Model 2 (with a data augmentation layer and 10% of training data).mp4 167.5 MB
5. Computer Vision and Convolutional Neural Networks in TensorFlow/20. Breaking our CNN model down part 10 Visualizing our augmented data.mp4 165.3 MB
8. Transfer Learning with TensorFlow Part 3 Scaling Up/14. Creating a confusion matrix for our model's 101 different classes.mp4 164.2 MB
4. Neural network classification in TensorFlow/18. Using callbacks to find a model's ideal learning rate.mp4 163.5 MB
3. Neural network regression with TensorFlow/25. Putting together what we've learned part 3 (improving our regression model).mp4 162.6 MB
5. Computer Vision and Convolutional Neural Networks in TensorFlow/7. Building an end to end CNN Model.mp4 162.6 MB
7. Transfer Learning in TensorFlow Part 2 Fine tuning/13. Building Model 1 (with a data augmentation layer and 1% of training data).mp4 160.4 MB
7. Transfer Learning in TensorFlow Part 2 Fine tuning/8. Getting a feature vector from our trained model.mp4 154.8 MB
4. Neural network classification in TensorFlow/15. Non-linearity part 5 Replicating non-linear activation functions from scratch.mp4 153.7 MB
6. Transfer Learning in TensorFlow Part 1 Feature extraction/10. Comparing Our Model's Results.mp4 150.9 MB
3. Neural network regression with TensorFlow/23. Putting together what we've learned part 1 (preparing a dataset).mp4 150.5 MB
4. Neural network classification in TensorFlow/26. Multi-class classification part 3 Building a multi-class classification model.mp4 149.7 MB
5. Computer Vision and Convolutional Neural Networks in TensorFlow/27. Multi-class CNN's part 1 Becoming one with the data.mp4 147.0 MB
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- 【影视】 [FreeCourseSite.com] Udemy - A Complete Guide on TensorFlow 2.0 using Keras API
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收录时间:2021-03-11
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16. Annex 2 - Convolutional Neural Networks Theory/7. Step 4 - Full Connection.mp4 203.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/5. LSTM Practical Intuition.mp4 196.5 MB
1. Introduction/1. Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit..mp4 153.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.srt 147.0 MB
16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.mp4 147.0 MB
7. Deep Reinforcement Learning Theory/9. Action Selection Policies.mp4 143.5 MB
17. Annex 3 - Recurrent Neural Networks Theory/4. LSTMs.mp4 143.1 MB
17. Annex 3 - Recurrent Neural Networks Theory/2. What are Recurrent Neural Networks.mp4 126.8 MB
16. Annex 2 - Convolutional Neural Networks Theory/9. Softmax & Cross-Entropy.mp4 123.6 MB
2. TensorFlow 2.0 Basics/1. From TensorFlow 1.x to TensorFlow 2.0.mp4 120.4 MB
7. Deep Reinforcement Learning Theory/8. Experience Replay.mp4 120.3 MB
15. Annex 1 - Artificial Neural Networks Theory/5. How do Neural Networks Learn.mp4 117.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/3. Vanishing Gradient.mp4 116.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/2. What are Convolutional Neural Networks.mp4 113.1 MB
7. Deep Reinforcement Learning Theory/6. Deep Q-Learning Intuition - Step 1.mp4 104.8 MB
15. Annex 1 - Artificial Neural Networks Theory/2. The Neuron.mp4 103.5 MB
16. Annex 2 - Convolutional Neural Networks Theory/3. Step 1 - Convolution.mp4 102.6 MB
7. Deep Reinforcement Learning Theory/5. Temporal Difference.mp4 101.8 MB
7. Deep Reinforcement Learning Theory/2. The Bellman Equation.mp4 99.7 MB
7. Deep Reinforcement Learning Theory/3. Markov Decision Process (MDP).mp4 98.9 MB
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[TutsNode.com] - Tensorflow 2 & KerasDeep Learning & Artificial Intelligence/8. Transfer Learning/2. Data Augmentation.mp4 102.1 MB
[TutsNode.com] - Tensorflow 2 & KerasDeep Learning & Artificial Intelligence/10. Generative Deep Learning/2. Neural Style Transfer Implementation part 1.mp4 92.2 MB
[TutsNode.com] - Tensorflow 2 & KerasDeep Learning & Artificial Intelligence/9. GAN/3. DCGAN Project.mp4 91.0 MB
[TutsNode.com] - Tensorflow 2 & KerasDeep Learning & Artificial Intelligence/5. CNN Neural Network/6. facial expression recognition 1.mp4 87.7 MB
[TutsNode.com] - Tensorflow 2 & KerasDeep Learning & Artificial Intelligence/8. Transfer Learning/1. CNN Transfer Learning.mp4 84.6 MB
[TutsNode.com] - Tensorflow 2 & KerasDeep Learning & Artificial Intelligence/5. CNN Neural Network/4. cat dog classification.mp4 83.5 MB
[TutsNode.com] - Tensorflow 2 & KerasDeep Learning & Artificial Intelligence/10. Generative Deep Learning/3. Neural Style Transfer Implementation part 2.mp4 80.0 MB
[TutsNode.com] - Tensorflow 2 & KerasDeep Learning & Artificial Intelligence/5. CNN Neural Network/8. leaf diseases 1.mp4 77.6 MB
[TutsNode.com] - Tensorflow 2 & KerasDeep Learning & Artificial Intelligence/6. RNN/3. Text classification.mp4 75.0 MB
[TutsNode.com] - Tensorflow 2 & KerasDeep Learning & Artificial Intelligence/7. Autoencoders/1. Introduction to Autoencoders.mp4 74.9 MB
[TutsNode.com] - Tensorflow 2 & KerasDeep Learning & Artificial Intelligence/5. CNN Neural Network/3. MNIST digit classification.mp4 72.4 MB
[TutsNode.com] - Tensorflow 2 & KerasDeep Learning & Artificial Intelligence/3. Neural Network and Tensorflow/2. Introduction to Neural Network.mp4 70.4 MB
[TutsNode.com] - Tensorflow 2 & KerasDeep Learning & Artificial Intelligence/4. Keras/3. Fashion MNIST Part 1.mp4 69.8 MB
[TutsNode.com] - Tensorflow 2 & KerasDeep Learning & Artificial Intelligence/7. Autoencoders/2. implementation of autoencoder.mp4 68.9 MB
[TutsNode.com] - Tensorflow 2 & KerasDeep Learning & Artificial Intelligence/4. Keras/4. Fashion MNIST Part 2.mp4 68.6 MB
[TutsNode.com] - Tensorflow 2 & KerasDeep Learning & Artificial Intelligence/4. Keras/5. Fashion MNIST Part 3.mp4 64.6 MB
[TutsNode.com] - Tensorflow 2 & KerasDeep Learning & Artificial Intelligence/3. Neural Network and Tensorflow/9. Gradient Descent.mp4 63.9 MB
[TutsNode.com] - Tensorflow 2 & KerasDeep Learning & Artificial Intelligence/4. Keras/2. CIFAR 10.mp4 62.2 MB
[TutsNode.com] - Tensorflow 2 & KerasDeep Learning & Artificial Intelligence/11. Crash Course on Data Science Libraries/1. Python for Data Analysis- Numpy.mp4 59.1 MB
[TutsNode.com] - Tensorflow 2 & KerasDeep Learning & Artificial Intelligence/6. RNN/1. RNN INTRODUCTION.mp4 58.5 MB
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- 【影视】 The Magic of Deep Learning with TensorFlow 2
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The Magic of Deep Learning with TensorFlow 2/1. Getting started with Tensorflow 2/2. Machine Learning Algorithm Part 1.mp4 113.0 MB
The Magic of Deep Learning with TensorFlow 2/3. Face Detection with TensorFlow 2/5. Buidling the Second Module classifier.py with TensorFlow 2.mp4 105.0 MB
The Magic of Deep Learning with TensorFlow 2/1. Getting started with Tensorflow 2/3. Machine Learning Algorithm Part 2.mp4 100.1 MB
The Magic of Deep Learning with TensorFlow 2/5. The Magic of TensorFlow 2/1. Detecting the faces in Vidoes Part 1.mp4 86.3 MB
The Magic of Deep Learning with TensorFlow 2/3. Face Detection with TensorFlow 2/3. Buidling the First Module preprocessing.py with TensorFlow 2 part 2.mp4 78.5 MB
The Magic of Deep Learning with TensorFlow 2/3. Face Detection with TensorFlow 2/4. Buidling the First Module preprocessing.py with TensorFlow 2 part 3.mp4 72.8 MB
The Magic of Deep Learning with TensorFlow 2/2. Diffrence Between TensorFlow 1.x and TensorFlow 2/3. Preprocessing Image Part 1.mp4 71.9 MB
The Magic of Deep Learning with TensorFlow 2/5. The Magic of TensorFlow 2/2. Detecting the faces in Vidoes Part 2.mp4 67.1 MB
The Magic of Deep Learning with TensorFlow 2/4. Yolo Detector with TensorFlow 2/2. The dataset creation.mp4 60.9 MB
The Magic of Deep Learning with TensorFlow 2/4. Yolo Detector with TensorFlow 2/3. Labelling the dataset and generate the annotation XML file.mp4 50.7 MB
The Magic of Deep Learning with TensorFlow 2/2. Diffrence Between TensorFlow 1.x and TensorFlow 2/1. Diffrence Between TensorFlow 1.x and TensorFlow 2 Part 1.mp4 49.3 MB
The Magic of Deep Learning with TensorFlow 2/2. Diffrence Between TensorFlow 1.x and TensorFlow 2/2. Diffrence Between TensorFlow 1.x and TensorFlow 2 Part 2.mp4 48.4 MB
The Magic of Deep Learning with TensorFlow 2/5. The Magic of TensorFlow 2/3. Yolo Object detector live stream.mp4 42.2 MB
The Magic of Deep Learning with TensorFlow 2/3. Face Detection with TensorFlow 2/2. Buidling the First Module preprocessing.py with TensorFlow 2 part 1.mp4 32.5 MB
The Magic of Deep Learning with TensorFlow 2/1. Getting started with Tensorflow 2/1. Installing TensorFlow 2.mp4 27.9 MB
The Magic of Deep Learning with TensorFlow 2/2. Diffrence Between TensorFlow 1.x and TensorFlow 2/4. Preprocessing Image Part 2.mp4 24.4 MB
The Magic of Deep Learning with TensorFlow 2/4. Yolo Detector with TensorFlow 2/4. Modifying and training your custom Yolo detector for the new object.mp4 20.6 MB
The Magic of Deep Learning with TensorFlow 2/3. Face Detection with TensorFlow 2/1. Introduction.mp4 16.1 MB
The Magic of Deep Learning with TensorFlow 2/3. Face Detection with TensorFlow 2/6. Buidling the Third Module data_preprocesses.py with TensorFlow 2.mp4 7.2 MB
The Magic of Deep Learning with TensorFlow 2/4. Yolo Detector with TensorFlow 2/1. Introduction.mp4 5.1 MB
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[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/04 Binary Classification with Artificial Neural Networks/014 Step 2 - Binary Classification.mp4 177.1 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/02 Introduction to Artificial Neural Networks (ANNs)/005 Activation Function.mp4 164.2 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/10 Project 3_ CNN for Predicting the Bank Customer Satisfaction/037 CNN for Predicting the Bank Customer Satisfaction Part 2.mp4 149.0 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/17 Natural Language Processing/073 Text Classification Part 2.mp4 146.8 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/03 Building the Artificial Neural Networks (ANNs)/009 Step 2 - Data Preprocessing.mp4 142.2 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/17 Natural Language Processing/072 Text Classification Part 1.mp4 137.4 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/06 Building Convolutional Neural Networks (CNNs)/022 Building Convolutional Neural Network Step 3.mp4 134.8 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/15 Project 6_ Google Stock Price Prediction with RNN and LSTM/056 Google Stock Price Prediction with RNN and LSTM Part 4.mp4 124.2 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/15 Project 6_ Google Stock Price Prediction with RNN and LSTM/053 Google Stock Price Prediction with RNN and LSTM Part 1.mp4 115.5 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/02 Introduction to Artificial Neural Networks (ANNs)/004 The Neuron.mp4 107.0 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/11 Project 4_ CNN for Credit Card Fraud Detection/041 CNN for Credit Card Fraud Detection Part 2.mp4 106.6 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/17 Natural Language Processing/068 Stop Words.mp4 103.3 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/09 Project 2_ CNN for Breast Cancer Detection/033 CNN for Breast Cancer Detection Part 1.mp4 101.5 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/05 Introduction to Convolutional Neural Networks (CNNs)/018 Convolutional Neural Network Part 1.mp4 100.9 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/07 CNN for Binary Image Classification/027 CNN for Binary Image Classification Step 3.mp4 99.9 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/20 Annex 3_ Data Visualization with Matplotlib/096 Matplotlib Part 4.mp4 95.6 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/11 Project 4_ CNN for Credit Card Fraud Detection/042 CNN for Credit Card Fraud Detection Part 3.mp4 95.5 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/20 Annex 3_ Data Visualization with Matplotlib/091 Matplotlib Part 1 - Functional Method.mp4 95.0 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/17 Natural Language Processing/065 Tokenization.mp4 91.0 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/11 Project 4_ CNN for Credit Card Fraud Detection/040 CNN for Credit Card Fraud Detection Part 1.mp4 89.7 MB
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06. Operationalize the model/04. Lab 4 demo and review.mp4 62.1 MB
06. Operationalize the model/09. Lab 5 demo and review.mp4 61.0 MB
05. Build the Model/04. Lab 3 -demo and review.mp4 59.7 MB
04. Create the dataset/04. Lab 2-demo and review.mp4 49.7 MB
07. Summary/01. Summary.mp4 39.6 MB
06. Operationalize the model/12. Lab Solution BigQuery ML.mp4 37.0 MB
06. Operationalize the model/16. Lab 6 -demo and review.mp4 35.1 MB
01. Welcome to the Course/02. Course Introduction.mp4 33.9 MB
06. Operationalize the model/18. Lab 7 -demo and review.mp4 30.7 MB
03. Explore the Data/07. Lab 1 demo and review.mp4 30.3 MB
03. Explore the Data/01. Exploring the dataset.mp4 27.6 MB
05. Build the Model/01. Build the model.mp4 27.5 MB
05. Build the Model/02. Lab 3 Intro -Creating a TensorFlow model.mp4 26.8 MB
01. Welcome to the Course/01. Intro to Specialization.mp4 19.2 MB
02. Machine Learning (ML) on Google Cloud Platform (GCP)/02. Fully managed ML.mp4 18.0 MB
03. Explore the Data/05. Lab 1 Intro -Exploring the dataset.mp4 17.7 MB
04. Create the dataset/01. Creating a dataset.mp4 17.6 MB
06. Operationalize the model/07. Lab 5 -Training on Cloud AI Platform.mp4 16.6 MB
02. Machine Learning (ML) on Google Cloud Platform (GCP)/01. Effective ML.mp4 14.6 MB
06. Operationalize the model/01. Operationalizing the model.mp4 14.5 MB
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14. Appendix Linear Algebra Fundamentals/11. Why is Linear Algebra Useful.mp4 151.3 MB
1. Welcome! Course introduction/1. Meet your instructors and why you should study machine learning.mp4 110.9 MB
13. Business case/4. Preprocessing the data.mp4 88.4 MB
13. Business case/1. Exploring the dataset and identifying predictors.mp4 69.5 MB
13. Business case/9. Setting an early stopping mechanism.mp4 52.2 MB
14. Appendix Linear Algebra Fundamentals/3. Linear Algebra and Geometry.mp4 52.2 MB
14. Appendix Linear Algebra Fundamentals/10. Dot Product of Matrices.mp4 51.8 MB
12. The MNIST example/6. Preprocess the data - shuffle and batch the data.mp4 43.6 MB
12. The MNIST example/10. Learning.mp4 42.9 MB
2. Introduction to neural networks/24. N-parameter gradient descent.mp4 41.4 MB
3. Setting up the working environment/9. Installing TensorFlow 2.mp4 40.6 MB
2. Introduction to neural networks/12. The linear model. Multiple inputs and multiple outputs.mp4 40.1 MB
14. Appendix Linear Algebra Fundamentals/8. Transpose of a Matrix.mp4 39.9 MB
5. TensorFlow - An introduction/5. Model layout - inputs, outputs, targets, weights, biases, optimizer and loss.mp4 36.4 MB
14. Appendix Linear Algebra Fundamentals/2. Scalars and Vectors.mp4 35.5 MB
14. Appendix Linear Algebra Fundamentals/1. What is a Matrix.mp4 35.2 MB
5. TensorFlow - An introduction/1. TensorFlow outline.mp4 35.2 MB
14. Appendix Linear Algebra Fundamentals/6. Addition and Subtraction of Matrices.mp4 34.2 MB
3. Setting up the working environment/2. Why Python and why Jupyter.mp4 33.6 MB
13. Business case/8. Learning and interpreting the result.mp4 32.7 MB
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01 Course Overview Installs and Setup/002 Course Setup and Installation.mp4 159.8 MB
13 Deployment/114 Flask Front End.mp4 156.9 MB
09 Recurrent Neural Networks - RNNs/088 Bonus - Multivariate Time Series - RNN and LSTMs.mp4 156.6 MB
09 Recurrent Neural Networks - RNNs/087 RNN Exercise - Solutions.mp4 155.3 MB
07 Basic Artificial Neural Networks - ANNs/057 Tensorboard.mp4 151.2 MB
07 Basic Artificial Neural Networks - ANNs/050 Keras Project Solutions - Exploratory Data Analysis.mp4 150.6 MB
07 Basic Artificial Neural Networks - ANNs/042 Keras Regression Code Along - Exploratory Data Analysis.mp4 143.7 MB
12 Generative Adversarial Networks/106 Creating a GAN - Part Three - Model Training.mp4 138.0 MB
09 Recurrent Neural Networks - RNNs/085 RNN on a Time Series - Part Two.mp4 137.4 MB
13 Deployment/115 Live Deployment to the Web.mp4 132.7 MB
07 Basic Artificial Neural Networks - ANNs/053 Keras Project Solutions - Categorical Data.mp4 131.1 MB
11 AutoEncoders/098 Autoencoder for Dimensionality Reduction.mp4 123.2 MB
07 Basic Artificial Neural Networks - ANNs/047 Keras Classification - Dealing with Overfitting and Evaluation.mp4 116.7 MB
01 Course Overview Installs and Setup/002 FINAL-TF2-FILES.zip 104.1 MB
01 Course Overview Installs and Setup/003 FINAL-TF2-FILES.zip 104.1 MB
08 Convolutional Neural Networks - CNNs/064 CNN on MNIST - Part Two - Creating and Training the Model.mp4 103.7 MB
07 Basic Artificial Neural Networks - ANNs/051 Keras Project Solutions - Dealing with Missing Data.mp4 101.5 MB
11 AutoEncoders/099 Autoencoder for Images - Part One.mp4 98.7 MB
04 Pandas Crash Course/017 Data Input and Output.mp4 98.0 MB
05 Visualization Crash Course/022 Seaborn Basics.mp4 96.3 MB
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05. Training neural networks with Tensorflow 2 and Keras Functional API/01. Neural Networks with Keras Functional API.mp4 35.1 MB
04. Training neural networks with Tensorflow 2 and the Keras Sequential API/02. Activation functions.mp4 25.6 MB
02. Introduction to TensorFlow/01. Introduction to Tensorflow.mp4 23.8 MB
04. Training neural networks with Tensorflow 2 and the Keras Sequential API/04. Neural Networks with Keras Sequential API.mp4 23.6 MB
03. Design and Build a TensorFlow Input Data Pipeline/03. Getting the data ready for model training.mp4 21.9 MB
02. Introduction to TensorFlow/03. Components of TensorFlow- Tensors and Variables.mp4 20.4 MB
04. Training neural networks with Tensorflow 2 and the Keras Sequential API/03. Activation functions- Pitfalls to avoid in Backpropagation.mp4 18.9 MB
05. Training neural networks with Tensorflow 2 and Keras Functional API/04. Regularization- Dropout.mp4 18.3 MB
06. Summary/01. Course Summary.mp4 17.0 MB
05. Training neural networks with Tensorflow 2 and Keras Functional API/02. Regularization- The Basics.mp4 16.6 MB
03. Design and Build a TensorFlow Input Data Pipeline/12. Training on Large Datasets with tf.data API.mp4 14.1 MB
03. Design and Build a TensorFlow Input Data Pipeline/02. Working in-memory and with files.mp4 13.2 MB
02. Introduction to TensorFlow/02. TensorFlow API Hierarchy.mp4 12.4 MB
02. Introduction to TensorFlow/05. Getting Started With GCP And Qwiklabs.mp4 11.3 MB
05. Training neural networks with Tensorflow 2 and Keras Functional API/03. Regularization- L1, L2, and Early Stopping.mp4 10.2 MB
05. Training neural networks with Tensorflow 2 and Keras Functional API/05. Serving models in the Cloud.mp4 9.6 MB
03. Design and Build a TensorFlow Input Data Pipeline/01. Overview.mp4 7.5 MB
01. Introduction to course/01. Intro to Course.mp4 6.2 MB
05. Training neural networks with Tensorflow 2 and Keras Functional API/06. Lab intro Keras Functional API.mp4 4.1 MB
03. Design and Build a TensorFlow Input Data Pipeline/15. Optional Lab Intro Feature Analysis Using TensorFlow Data Validation and Facets.mp4 3.0 MB
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Chapter 3 Feedforward Artificial Neural Networks/004. Activation Functions.mp4 64.7 MB
Chapter 3 Feedforward Artificial Neural Networks/009. ANN for Regression.mp4 58.7 MB
Chapter 2 Machine Learning and Neurons/001. What Is Machine Learning.mp4 56.1 MB
Chapter 3 Feedforward Artificial Neural Networks/006. How to Represent Images.mp4 52.0 MB
Chapter 2 Machine Learning and Neurons/002. Code Preparation (Classification Theory).mp4 50.7 MB
Chapter 2 Machine Learning and Neurons/005. Regression Notebook.mp4 50.0 MB
Chapter 2 Machine Learning and Neurons/003. Classification Notebook.mp4 46.9 MB
Chapter 3 Feedforward Artificial Neural Networks/007. Code Preparation (Artificial Neural Networks).mp4 44.2 MB
Chapter 5 In-Depth Gradient Descent/005. Adam Optimization (Part 1).mp4 44.1 MB
Chapter 5 In-Depth Gradient Descent/006. Adam Optimization (Part 2).mp4 42.4 MB
Chapter 3 Feedforward Artificial Neural Networks/008. ANN for Image Classification.mp4 42.1 MB
Chapter 3 Feedforward Artificial Neural Networks/003. The Geometrical Picture.mp4 41.3 MB
Chapter 2 Machine Learning and Neurons/007. How Does a Model Learn .mp4 40.4 MB
Chapter 2 Machine Learning and Neurons/006. The Neuron.mp4 35.7 MB
Chapter 3 Feedforward Artificial Neural Networks/005. Multiclass Classification.mp4 35.6 MB
Chapter 3 Feedforward Artificial Neural Networks/002. Forward Propagation.mp4 35.4 MB
Chapter 5 In-Depth Gradient Descent/004. Variable and Adaptive Learning Rates.mp4 34.2 MB
Chapter 4 In-Depth Loss Functions/001. Mean Squared Error.mp4 31.8 MB
Chapter 2 Machine Learning and Neurons/008. Making Predictions.mp4 31.2 MB
Chapter 5 In-Depth Gradient Descent/003. Momentum.mp4 30.2 MB
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3. Natural language processing/6. Q&A and information retrieval 2.mp4 162.5 MB
2. Computer vision/5. Image classification 4.mp4 114.3 MB
2. Computer vision/7. Object detection 1.mp4 109.9 MB
2. Computer vision/2. Image classification 1.mp4 107.9 MB
2. Computer vision/14. Image extension using GAN 2.mp4 99.0 MB
3. Natural language processing/8. Q&A and information retrieval 4.mp4 96.5 MB
2. Computer vision/17. Action recognition 3.mp4 95.5 MB
3. Natural language processing/9. Q&A and information retrieval 5.mp4 92.7 MB
2. Computer vision/9. Object detection 3.mp4 90.5 MB
2. Computer vision/6. Image classification 5.mp4 89.9 MB
3. Natural language processing/3. Text classification 2.mp4 87.7 MB
2. Computer vision/15. Action recognition 1.mp4 85.5 MB
3. Natural language processing/7. Q&A and information retrieval 3.mp4 84.3 MB
1. Introduction/1. Course content.mp4 83.2 MB
2. Computer vision/18. Action recognition 4.mp4 79.1 MB
2. Computer vision/3. Image classification 2.mp4 71.6 MB
2. Computer vision/4. Image classification 3.mp4 68.4 MB
3. Natural language processing/10. Audio classification 1.mp4 68.2 MB
4. Extra content 1 Artificial neural networks/8. Bias, error, stochastic gradient descent, and more parameters.mp4 66.5 MB
2. Computer vision/11. Style transfer 2.mp4 65.5 MB
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01.Welcome! Course introduction/0101.Meet your instructors and why you should study machine learning.mp4 88.9 MB
06.Going deeper Introduction to deep neural networks/0603.Understanding deep nets in depth.mp4 61.0 MB
02.Introduction to neural networks/0212.N-parameter gradient descent.mp4 60.4 MB
02.Introduction to neural networks/0211.One parameter gradient descent.mp4 59.1 MB
06.Going deeper Introduction to deep neural networks/0607.Backpropagation.mp4 55.3 MB
03.Setting up the working environment/0306.Installing TensorFlow 2.mp4 53.7 MB
02.Introduction to neural networks/0201.Introduction to neural networks.mp4 48.0 MB
12.Business case/1204.Preprocessing the data.mp4 46.7 MB
02.Introduction to neural networks/0206.The linear model. Multiple inputs and multiple outputs.mp4 44.3 MB
05.TensorFlow - An introduction/0501.TensorFlow outline.mp4 44.0 MB
02.Introduction to neural networks/0203.Types of machine learning.mp4 42.8 MB
10.Preprocessing/1003.Standardization.mp4 42.3 MB
13.Conclusion/1305.An overview of non-NN approaches.mp4 42.1 MB
01.Welcome! Course introduction/0102.What does the course cover.mp4 41.0 MB
13.Conclusion/1301.See how much you have learned.mp4 40.8 MB
06.Going deeper Introduction to deep neural networks/0604.Why do we need non-linearities.mp4 39.8 MB
06.Going deeper Introduction to deep neural networks/0605.Activation functions.mp4 39.8 MB
05.TensorFlow - An introduction/0502.TensorFlow 2 intro.mp4 39.7 MB
07.Overfitting/0703.Training and validation.mp4 39.3 MB
09.Gradient descent and learning rates/0904.Learning rate schedules.mp4 38.9 MB
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~Get Your Files Here !/2. Understanding and Preparing Time Series Data/7. Demo - Techniques for Identifying and Reducing Sequenc.mp4 15.0 MB
~Get Your Files Here !/4. Implementing Advanced Techniques for Time Series Analysis/5. Demo - Predictive Modelling with TensorFl.mp4 14.8 MB
~Get Your Files Here !/3. Training and Evaluating Time Series Models/4. Demo - Implementing Model Training and Evaluation.mp4 12.5 MB
~Get Your Files Here !/2. Understanding and Preparing Time Series Data/5. Demo - Time Series Data Preparation.mp4 12.1 MB
~Get Your Files Here !/2. Understanding and Preparing Time Series Data/2. Defining Time Series and Sequences.mp4 12.0 MB
~Get Your Files Here !/3. Training and Evaluating Time Series Models/8. Demo - Implementing a CNN for Time Series Prediction.mp4 10.4 MB
~Get Your Files Here !/2. Understanding and Preparing Time Series Data/3. Demo - Time Series Visualization.mp4 9.5 MB
~Get Your Files Here !/3. Training and Evaluating Time Series Models/6. Demo - Building an RNN for Time Series Prediction.mp4 9.1 MB
~Get Your Files Here !/4. Implementing Advanced Techniques for Time Series Analysis/3. Demo - Comparing Trailing Windows.mp4 8.9 MB
~Get Your Files Here !/2. Understanding and Preparing Time Series Data/1. Intended Outcome and Prerequisites.mp4 6.0 MB
~Get Your Files Here !/3. Training and Evaluating Time Series Models/3. Techniques for Model Training and Hyperparameter Tuning.mp4 5.9 MB
~Get Your Files Here !/2. Understanding and Preparing Time Series Data/4. Data Preparation Techniques for Time Series Learning.mp4 5.9 MB
~Get Your Files Here !/3. Training and Evaluating Time Series Models/1. Overview of Error Metrics.mp4 5.9 MB
~Get Your Files Here !/4. Implementing Advanced Techniques for Time Series Analysis/6. Advanced Forecasting Techniques with Tens.mp4 5.5 MB
~Get Your Files Here !/3. Training and Evaluating Time Series Models/7. Implementing Convolutional Neural Networks (CNNs).mp4 5.4 MB
~Get Your Files Here !/4. Implementing Advanced Techniques for Time Series Analysis/1. Understanding Data Windowing in Time Seri.mp4 5.3 MB
~Get Your Files Here !/1. Course Overview/1. Course Overview.mp4 5.1 MB
~Get Your Files Here !/3. Training and Evaluating Time Series Models/5. Implementing Recurrent Neural Networks (RNNs).mp4 4.9 MB
~Get Your Files Here !/2. Understanding and Preparing Time Series Data/6. Addressing Sequence Bias in Time Series Analysis.mp4 4.7 MB
~Get Your Files Here !/4. Implementing Advanced Techniques for Time Series Analysis/4. Leveraging TensorFlow for Forecasting.mp4 3.9 MB
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01 - Introduction/001 Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit.mp4 153.4 MB
02 - TensorFlow 2.0 Basics/001 From TensorFlow 1.x to TensorFlow 2.0.mp4 120.4 MB
17 - Annex 3 - Recurrent Neural Networks Theory/005 LSTM Practical Intuition.mp4 112.7 MB
17 - Annex 3 - Recurrent Neural Networks Theory/004 LSTMs.mp4 93.2 MB
16 - Annex 2 - Convolutional Neural Networks Theory/005 Step 2 - Max Pooling.mp4 91.7 MB
17 - Annex 3 - Recurrent Neural Networks Theory/003 Vanishing Gradient.mp4 90.4 MB
16 - Annex 2 - Convolutional Neural Networks Theory/002 What are Convolutional Neural Networks.mp4 74.5 MB
16 - Annex 2 - Convolutional Neural Networks Theory/003 Step 1 - Convolution.mp4 68.8 MB
10 - Dataset Preprocessing with TensorFlow Transform (TFT)/005 Dataset preprocessing pipeline.mp4 62.7 MB
16 - Annex 2 - Convolutional Neural Networks Theory/007 Step 4 - Full Connection.mp4 61.4 MB
17 - Annex 3 - Recurrent Neural Networks Theory/002 What are Recurrent Neural Networks.mp4 60.3 MB
04 - Convolutional Neural Networks/002 Building the Convolutional Neural Network.mp4 59.3 MB
07 - Deep Reinforcement Learning Theory/009 Action Selection Policies.mp4 57.0 MB
16 - Annex 2 - Convolutional Neural Networks Theory/009 Softmax & Cross-Entropy.mp4 53.9 MB
07 - Deep Reinforcement Learning Theory/002 The Bellman Equation.mp4 50.6 MB
06 - Transfer Learning and Fine Tuning/001 What is Transfer Learning.mp4 48.7 MB
06 - Transfer Learning and Fine Tuning/002 Project Setup.mp4 46.6 MB
15 - Annex 1 - Artificial Neural Networks Theory/002 The Neuron.mp4 45.8 MB
15 - Annex 1 - Artificial Neural Networks Theory/005 How do Neural Networks Learn.mp4 45.4 MB
07 - Deep Reinforcement Learning Theory/003 Markov Decision Process (MDP).mp4 44.4 MB
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~Get Your Files Here !/1. Chapter 1/18. 14. Classes And Objects.mp4 234.1 MB
~Get Your Files Here !/1. Chapter 1/15. 11. Loops.mp4 175.2 MB
~Get Your Files Here !/1. Chapter 1/7. 03. Operators.mp4 169.3 MB
~Get Your Files Here !/1. Chapter 1/19. 15. Inheritance Examples.mp4 137.0 MB
~Get Your Files Here !/1. Chapter 1/14. 10. If Statement Examples.mp4 123.8 MB
~Get Your Files Here !/4. 07 Data analysis and transformation on blood cell data/3. 02 Clean Data With Missing Values.mp4 123.2 MB
~Get Your Files Here !/1. Chapter 1/9. 05. List Examples.mp4 115.1 MB
~Get Your Files Here !/1. Chapter 1/5. 01. Variables.mp4 111.6 MB
~Get Your Files Here !/10. 13 Prepare heart disease data for machine learning/2. 02 Clean And Preprocess Heart Disease Data For Machine Learning.mp4 109.1 MB
~Get Your Files Here !/3. 06 Build Regression Machine Learning Models to Detect Diabetes/3. 04 Select Top Features Via Variance Threshold.mp4 108.0 MB
~Get Your Files Here !/1. Chapter 1/11. 07. Dictionaries Examples.mp4 91.5 MB
~Get Your Files Here !/1. Chapter 1/16. 12. Functions.mp4 90.6 MB
~Get Your Files Here !/1. Chapter 1/27. 02 What Is Regression.mp4 87.8 MB
~Get Your Files Here !/10. 13 Prepare heart disease data for machine learning/1. 01 Load Data Via Data File.mp4 87.1 MB
~Get Your Files Here !/2. 05 Build a K Nearest neighbors regression model to predict diabetes/2. 01 Load And Analyze Data.mp4 84.3 MB
~Get Your Files Here !/1. Chapter 1/20. 16. Static Members Examples.mp4 82.4 MB
~Get Your Files Here !/1. Chapter 1/17. 13. Parameters And Return Values Examples.mp4 82.3 MB
~Get Your Files Here !/2. 05 Build a K Nearest neighbors regression model to predict diabetes/4. 02 Build A K Nearest Neighbors Regression Model To Predict Diabetes.mp4 81.3 MB
~Get Your Files Here !/4. 07 Data analysis and transformation on blood cell data/2. 01 Load And Analyze Blood Cell Data.mp4 78.6 MB
~Get Your Files Here !/13. 16 Build a neural network to find malaria in cells/6. 05 Train And Evaluate Model Accuracy.mp4 76.6 MB
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~Get Your Files Here !/02 Installation/001 Installation of Tensorflow.mp4 95.4 MB
~Get Your Files Here !/02 Installation/002 Basic Data Types for Tensorflow.mp4 65.4 MB
~Get Your Files Here !/03 Implementing Linear Model/003 Optimization of Variable.mp4 62.8 MB
~Get Your Files Here !/04 Addition and Random Number Calculation/002 Naming the Variable.mp4 62.5 MB
~Get Your Files Here !/03 Implementing Linear Model/004 Implementing the Constructor Variable.mp4 62.3 MB
~Get Your Files Here !/01 Introduction/001 Introduction to Tensorflow with Python.mp4 61.1 MB
~Get Your Files Here !/03 Implementing Linear Model/002 Creating a Python File.mp4 50.5 MB
~Get Your Files Here !/04 Addition and Random Number Calculation/001 Printing the Variable Result.mp4 30.9 MB
~Get Your Files Here !/03 Implementing Linear Model/001 Implementing Simple Linear Model.mp4 29.1 MB
~Get Your Files Here !/03 Implementing Linear Model/004 Implementing the Constructor Variable.mp4.vtx 545.8 kB
~Get Your Files Here !/01 Introduction/001 Introduction to Tensorflow with Python.en.srt 15.7 kB
~Get Your Files Here !/02 Installation/001 Installation of Tensorflow.en.srt 15.2 kB
~Get Your Files Here !/02 Installation/002 Basic Data Types for Tensorflow.en.srt 15.0 kB
~Get Your Files Here !/03 Implementing Linear Model/003 Optimization of Variable.en.srt 11.8 kB
~Get Your Files Here !/03 Implementing Linear Model/004 Implementing the Constructor Variable.en.srt 11.0 kB
~Get Your Files Here !/03 Implementing Linear Model/002 Creating a Python File.en.srt 9.2 kB
~Get Your Files Here !/04 Addition and Random Number Calculation/002 Naming the Variable.en.srt 9.1 kB
~Get Your Files Here !/03 Implementing Linear Model/001 Implementing Simple Linear Model.en.srt 8.1 kB
~Get Your Files Here !/04 Addition and Random Number Calculation/001 Printing the Variable Result.en.srt 5.9 kB
~Get Your Files Here !/Bonus Resources.txt 357 Bytes
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