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04 - Introduction to Optimisation and the Gradient Descent Algorithm/007 [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1).mp4 240.6 MB
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10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/012 Model Evaluation and the Confusion Matrix.mp4 202.6 MB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/009 Understanding the Learning Rate.mp4 199.4 MB
03 - Python Programming for Data Science and Machine Learning/008 [Python] - Module Imports.mp4 195.9 MB
12 - Serving a Tensorflow Model through a Website/007 Loading a Tensorflow.js Model and Starting your own Server.mp4 183.9 MB
05 - Predict House Prices with Multivariable Linear Regression/014 Working with Seaborn Pairplots & Jupyter Microbenchmarking Techniques.mp4 183.7 MB
10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/010 Use the Model to Make Predictions.mp4 182.3 MB
11 - Use Tensorflow to Classify Handwritten Digits/012 Different Model Architectures Experimenting with Dropout.mp4 182.3 MB
12 - Serving a Tensorflow Model through a Website/009 Styling an HTML Canvas.mp4 181.1 MB
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10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/009 Use Regularisation to Prevent Overfitting Early Stopping & Dropout Techniques.mp4 159.9 MB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/010 How to Create 3-Dimensional Charts.mp4 159.4 MB
08 - Test and Evaluate a Naive Bayes Classifier Part 3/006 Visualising the Decision Boundary.mp4 156.7 MB
12 - Serving a Tensorflow Model through a Website/013 Resizing and Adding Padding to Images.mp4 155.0 MB
08 - Test and Evaluate a Naive Bayes Classifier Part 3/011 A Naive Bayes Implementation using SciKit Learn.mp4 152.8 MB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/008 [Python] - Tuples and the Pitfalls of Optimisation (Part 2).mp4 152.3 MB
03 - Python Programming for Data Science and Machine Learning/013 How to Make Sense of Python Documentation for Data Visualisation.mp4 144.8 MB

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【影视】 [Udemy] Complete Machine Learning & Data Science with Python A-Z (05.2021)

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4. Linear Regression Algorithm/5. Linear Regression Algorithm Project Solutions.mp4 207.1 MB
4. Linear Regression Algorithm/2. Linear Regression Algorithm With Python Part 1.mp4 173.8 MB
7. K Nearest Neighbors Algorithm/4. K Nearest Neighbors Algorithm Project Solutions.mp4 151.4 MB
7. K Nearest Neighbors Algorithm/2. K Nearest Neighbors Algorithm With Python.mp4 147.2 MB
9. Support Vector Machine Algorithm/2. Support Vector Machines Algorithm With Python.mp4 143.3 MB
11. K Means Clustering Algorithm/4. K Means Clustering Algorithm Project Solutions.mp4 134.8 MB
13. Principal Component Analysis (PCA)/2. Principal Component Analysis (PCA) With Python.mp4 133.1 MB
6. Logistic Regression Algorithm/3. Logistic Regression Algorithm With Python Part 2.mp4 120.4 MB
6. Logistic Regression Algorithm/6. Logistic Regression Algorithm Project Solutions.mp4 119.8 MB
2. Evalution Metrics/2. Evaluating Performance Classification Error Metrics.mp4 117.6 MB
6. Logistic Regression Algorithm/2. Logistic Regression Algorithm With Python Part 1.mp4 115.8 MB
8. Decision Trees And Random Forest Algorithm/4. Decision Trees And Random Forest Algorithm Project Solutions Part 1.mp4 111.0 MB
9. Support Vector Machine Algorithm/4. Support Vector Machines Algorithm Project Solutions.mp4 102.7 MB
14. Recommender System Algorithm/2. Recommender System Algorithm With Python Part 1.mp4 98.6 MB
14. Recommender System Algorithm/3. Recommender System Algorithm With Python Part 2.mp4 97.6 MB
6. Logistic Regression Algorithm/1. Logistic Regression Algorithm Theory.mp4 96.0 MB
11. K Means Clustering Algorithm/2. K Means Clustering Algorithm With Python.mp4 93.4 MB
8. Decision Trees And Random Forest Algorithm/2. Decision Trees And Random Forest Algorithm With Python.mp4 90.4 MB
8. Decision Trees And Random Forest Algorithm/5. Decision Trees And Random Forest Algorithm Project Solutions Part 2.mp4 88.5 MB
2. Evalution Metrics/4. Machine Learning With Python.mp4 70.0 MB

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[TutsNode.com] - Machine Learning Crash Course/2 Supervised Learning/4-Naive Bayes Optimized.mp4.mp4 117.3 MB
[TutsNode.com] - Machine Learning Crash Course/4 Deep Learning/14-RNN.mp4.mp4 113.8 MB
[TutsNode.com] - Machine Learning Crash Course/2 Supervised Learning/3-Performance.mp4.mp4 99.4 MB
[TutsNode.com] - Machine Learning Crash Course/6 Ranking/17-Learning To Rank.mp4.mp4 90.0 MB
[TutsNode.com] - Machine Learning Crash Course/2 Supervised Learning/9-SVM.mp4.mp4 89.7 MB
[TutsNode.com] - Machine Learning Crash Course/2 Supervised Learning/6-Decision Trees.mp4.mp4 89.0 MB
[TutsNode.com] - Machine Learning Crash Course/2 Supervised Learning/2-Naive Bayes.mp4.mp4 84.3 MB
[TutsNode.com] - Machine Learning Crash Course/5 Recommender Systems/16-CollaborativeContent Filtering.mp4.mp4 81.8 MB
[TutsNode.com] - Machine Learning Crash Course/2 Supervised Learning/7- Linear Regression.mp4.mp4 71.9 MB
[TutsNode.com] - Machine Learning Crash Course/3 Unsupervised Learning/11-Singular Value Decomposition.mp4.mp4 67.1 MB
[TutsNode.com] - Machine Learning Crash Course/2 Supervised Learning/5-KNN.mp4.mp4 64.1 MB
[TutsNode.com] - Machine Learning Crash Course/3 Unsupervised Learning/10-K-means.mp4.mp4 63.2 MB
[TutsNode.com] - Machine Learning Crash Course/4 Deep Learning/15-GAN.mp4.mp4 60.8 MB
[TutsNode.com] - Machine Learning Crash Course/1 Introduction/0-Introduction.mp4.mp4 25.0 MB
[TutsNode.com] - Machine Learning Crash Course/1 Introduction/1-Prerequisites.mp4.mp4 22.0 MB
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【影视】 [ FreeCourseWeb.com ] Oreilly - Managing Machine Learning Projects, Video Edition

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~Get Your Files Here !/052. Chapter 8. Testing processes.mp4 73.3 MB
~Get Your Files Here !/038. Chapter 6. EDA, ethics, and baseline evaluations.mp4 61.4 MB
~Get Your Files Here !/060. Chapter 9. Implementing the production system.mp4 59.8 MB
~Get Your Files Here !/016. Chapter 3. Create an estimate.mp4 51.8 MB
~Get Your Files Here !/043. Chapter 6. The Bike Shop Pre-modelling.mp4 49.6 MB
~Get Your Files Here !/035. Chapter 5. Building data pipelines.mp4 47.0 MB
~Get Your Files Here !/033. Chapter 5. Understanding the data.mp4 41.5 MB
~Get Your Files Here !/055. Chapter 8. The Bike Shop sprint 2.mp4 38.9 MB
~Get Your Files Here !/058. Chapter 9. Types of ML implementations.mp4 32.8 MB
~Get Your Files Here !/069. Chapter 10. Off your hands and into production.mp4 32.2 MB
~Get Your Files Here !/046. Chapter 7. Feature engineering and data augmentation.mp4 31.9 MB
~Get Your Files Here !/030. Chapter 4. Bike Shop project setup.mp4 31.9 MB
~Get Your Files Here !/019. Chapter 3. The Bike Shop pre-sales.mp4 30.2 MB
~Get Your Files Here !/009. Chapter 2. Project requirements.mp4 28.9 MB
~Get Your Files Here !/048. Chapter 7. Making models with ML.mp4 28.7 MB
~Get Your Files Here !/053. Chapter 8. Model selection.mp4 27.3 MB
~Get Your Files Here !/026. Chapter 4. The data story.mp4 27.1 MB
~Get Your Files Here !/034. Chapter 5. Business problem refinement, UX, and application design.mp4 25.9 MB
~Get Your Files Here !/061. Chapter 9. Logging, monitoring, management, feedback, and documentation.mp4 22.5 MB
~Get Your Files Here !/012. Chapter 2. Corporate responsibility, regulation, and ethical considerations.mp4 21.2 MB

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