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【影视】 [CourseClub.NET] Lynda - Learning 3D Graphics Web Three js

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05 Animation/006 Animation rig, part 2.mp4 48.3 MB
05 Animation/007 Tween.js.mp4 34.3 MB
09 Post-Processing/002 EffectComposer.mp4 32.7 MB
07 Geometries/002 Manipulating vertices.mp4 30.5 MB
08 Particles/002 Animating the particle system.mp4 26.9 MB
05 Animation/002 Math.sin() and Math.cos().mp4 26.8 MB
08 Particles/001 Creating a particle system.mp4 24.8 MB
05 Animation/005 Animation rig.mp4 23.8 MB
06 Materials and Textures/004 Texture maps.mp4 23.8 MB
02 Building a Simple Scene/004 Populate the scene.mp4 21.4 MB
07 Geometries/001 Primitive geometries.mp4 20.9 MB
04 Lights/008 DirectionalLight.mp4 20.3 MB
08 Particles/003 Particle system from geometry.mp4 20.2 MB
06 Materials and Textures/006 Environment maps.mp4 20.0 MB
04 Lights/007 SpotLight.mp4 19.9 MB
07 Geometries/003 External geometries.mp4 18.6 MB
04 Lights/002 Light types.mp4 16.7 MB
02 Building a Simple Scene/005 Create a ground plane.mp4 16.2 MB
03 Three.js Scene Object/003 Other Object3D properties.mp4 15.9 MB
06 Materials and Textures/002 MeshLambertMaterial and MeshPhongMaterial.mp4 13.9 MB

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【影视】 [FreeCourseSite.com] Udemy - Complete 2020 Data Science & Machine Learning Bootcamp

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4. Introduction to Optimisation and the Gradient Descent Algorithm/8. [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1).mp4 305.5 MB
4. Introduction to Optimisation and the Gradient Descent Algorithm/6. [Python] - Loops and the Gradient Descent Algorithm.mp4 301.4 MB
10. Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/12. Model Evaluation and the Confusion Matrix.mp4 264.1 MB
5. Predict House Prices with Multivariable Linear Regression/32. Build a Valuation Tool (Part 3) Docstrings & Creating your own Python Module.mp4 256.0 MB
4. Introduction to Optimisation and the Gradient Descent Algorithm/10. Understanding the Learning Rate.mp4 248.1 MB
12. Serving a Tensorflow Model through a Website/12. Introduction to OpenCV.mp4 246.8 MB
3. Python Programming for Data Science and Machine Learning/10. [Python] - Module Imports.mp4 243.3 MB
12. Serving a Tensorflow Model through a Website/14. Calculating the Centre of Mass and Shifting the Image.mp4 234.1 MB
4. Introduction to Optimisation and the Gradient Descent Algorithm/9. [Python] - Tuples and the Pitfalls of Optimisation (Part 2).mp4 229.6 MB
10. Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/10. Use the Model to Make Predictions.mp4 228.9 MB
5. Predict House Prices with Multivariable Linear Regression/14. Working with Seaborn Pairplots & Jupyter Microbenchmarking Techniques.mp4 224.8 MB
11. Use Tensorflow to Classify Handwritten Digits/12. Different Model Architectures Experimenting with Dropout.mp4 224.1 MB
8. Test and Evaluate a Naive Bayes Classifier Part 3/6. Visualising the Decision Boundary.mp4 215.3 MB
8. Test and Evaluate a Naive Bayes Classifier Part 3/11. A Naive Bayes Implementation using SciKit Learn.mp4 204.6 MB
4. Introduction to Optimisation and the Gradient Descent Algorithm/11. How to Create 3-Dimensional Charts.mp4 202.9 MB
10. Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/9. Use Regularisation to Prevent Overfitting Early Stopping & Dropout Techniques.mp4 200.8 MB
12. Serving a Tensorflow Model through a Website/7. Loading a Tensorflow.js Model and Starting your own Server.mp4 197.2 MB
12. Serving a Tensorflow Model through a Website/9. Styling an HTML Canvas.mp4 196.5 MB
12. Serving a Tensorflow Model through a Website/16. Adding the Game Logic.mp4 181.2 MB
12. Serving a Tensorflow Model through a Website/10. Drawing on an HTML Canvas.mp4 180.3 MB

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【影视】 [DesireCourse.Net] Udemy - Machine Learning Basics Classification models in Python

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2. Introduction to Machine Learning/1. Introduction to Machine Learning.mp4 129.8 MB
5. Data Preprocessing/7. EDD in Python.mp4 101.8 MB
5. Data Preprocessing/3. The Dataset and the Data Dictionary.mp4 91.9 MB
6. Classification Models/21. K-Nearest Neighbors classifier.mp4 87.6 MB
3. Basics of Statistics/3. Describing data Graphically.mp4 86.2 MB
4. Setting up Python and Jupyter Notebook/5. Strings in Python Python Basics.mp4 84.5 MB
4. Setting up Python and Jupyter Notebook/6. Lists, Tuples and Directories Python Basics.mp4 77.2 MB
4. Setting up Python and Jupyter Notebook/2. Opening Jupyter Notebook.mp4 76.6 MB
6. Classification Models/11. Making Confusion Matrix in Python.mp4 67.9 MB
6. Classification Models/4. Training a Simple Logistic Model in Python.mp4 64.2 MB
5. Data Preprocessing/10. Outlier treatment in Python.mp4 61.3 MB
4. Setting up Python and Jupyter Notebook/8. Working with Pandas Library of Python.mp4 59.1 MB
4. Setting up Python and Jupyter Notebook/7. Working with Numpy Library of Python.mp4 56.7 MB
6. Classification Models/23. K-Nearest Neighbors in Python Part 2.mp4 54.5 MB
4. Setting up Python and Jupyter Notebook/3. Introduction to Jupyter.mp4 53.8 MB
4. Setting up Python and Jupyter Notebook/9. Working with Seaborn Library of Python.mp4 51.2 MB
6. Classification Models/15. Linear Discriminant Analysis.mp4 51.0 MB
6. Classification Models/25. Understanding the results of classification models.mp4 48.2 MB
6. Classification Models/22. K-Nearest Neighbors in Python Part 1.mp4 48.1 MB
6. Classification Models/18. Test-Train Split.mp4 47.9 MB

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【影视】 [DesireCourse.Net] Udemy - Python for Data Science and Machine Learning Bootcamp

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26. Neural Nets and Deep Learning/8. Tensorflow Estimators.mp4 164.3 MB
26. Neural Nets and Deep Learning/10. Deep Learning Project - Solutions.mp4 99.2 MB
26. Neural Nets and Deep Learning/7. MNIST - Part Two.mp4 98.7 MB
2. Environment Set-Up/1. Python Environment Setup.mp4 80.1 MB
27. APPENDIX OLD TENSORFLOW VIDEOS (Version 0.8)/1. TensorFlow Installation.mp4 72.6 MB
25. Big Data and Spark with Python/7. EC2 Instance Set-Up.mp4 66.0 MB
25. Big Data and Spark with Python/9. PySpark Setup.mp4 63.3 MB
26. Neural Nets and Deep Learning/6. MNIST - Part One.mp4 61.2 MB
25. Big Data and Spark with Python/12. RDD Transformations and Actions.mp4 58.4 MB
18. K Nearest Neighbors/4. KNN Project Solutions.mp4 55.2 MB
1. Course Introduction/3.1 Py_DS_ML_Bootcamp-master.zip.zip 55.0 MB
2. Environment Set-Up/1.1 Py-DS-ML-Bootcamp-master.zip.zip 55.0 MB
3. Jupyter Overview/2.1 Py-DS-ML-Bootcamp-master.zip.zip 55.0 MB
9. Python for Data Visualization - Seaborn/2. Distribution Plots.mp4 53.9 MB
11. Python for Data Visualization - Plotly and Cufflinks/2. Plotly and Cufflinks.mp4 53.6 MB
13. Data Capstone Project/4. 911 Calls Solutions - Part 2.mp4 52.2 MB
24. Natural Language Processing/6. NLP Project Solutions.mp4 50.4 MB
20. Support Vector Machines/2. Support Vector Machines with Python.mp4 49.8 MB
13. Data Capstone Project/7. Finance Project - Solutions Part 1.mp4 49.6 MB
21. K Means Clustering/4. K Means Project Solutions.mp4 49.4 MB

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【音乐】 Trust Genics - 2020 - Accelerated Learning (How-To)

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Accelerated Learning & Memory Improvement (Unabridged).mp3 128.8 MB
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【压缩文件】 [ FreeCourseWeb.com ] Skillshare - Deep Learning - The Foundations for Absolute Beginners.zip

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[ FreeCourseWeb.com ] Skillshare - Deep Learning - The Foundations for Absolute Beginners.zip 323.7 MB

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【影视】 [CourseClub.ME] A Cloud Guru - AWS Certified Machine Learning - Specialty 2020

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07 Algorithms/014 Algorithms Lab.mp4 205.5 MB
08 Evaluation and Optimization/007 Evaluation and Optimization Lab.mp4 172.3 MB
09 Implementation and Operations/009 Implementation and Operations Lab.mp4 172.1 MB
05 Data Analysis and Visualization/009 Data Analysis and Visualization Lab.mp4 157.2 MB
06 Modeling/007 Modeling Lab.mp4 151.0 MB
03 Streaming Data Collection/008 Streaming Data Collection Lab.mp4 131.6 MB
04 Data Preparation/011 Data Preparation Lab.mp4 109.0 MB
04 Data Preparation/004 Text Feature Engineering.mp4 61.4 MB
02 Data Collection/004 Machine Learning Data Terminology.mp4 60.0 MB
04 Data Preparation/009 Helper Tools.mp4 56.0 MB
08 Evaluation and Optimization/004 Evaluating Model Accuracy.mp4 53.4 MB
07 Algorithms/002 OPTIONAL - Why do we call them Algorithms.mp4 52.1 MB
06 Modeling/004 SageMaker Modeling.mp4 51.2 MB
07 Algorithms/003 Concepts.mp4 49.6 MB
07 Algorithms/004 Regression.mp4 48.8 MB
03 Streaming Data Collection/003 Kinesis Data Streams.mp4 47.8 MB
09 Implementation and Operations/002 Concepts.mp4 45.2 MB
09 Implementation and Operations/006 Security.mp4 45.0 MB
06 Modeling/005 SageMaker Training.mp4 40.9 MB
02 Data Collection/002 Concepts.mp4 38.9 MB

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2.3-c_9.0_new_features.mkv 37.5 MB
2.5-visual_studio_updates.mkv 17.9 MB
2.4-core_apis_and_the_runtime_updates.mkv 16.0 MB
2.7-entity_framework_new_features.mkv 15.7 MB
2.2-.net_5_and_related_frameworks.mkv 14.9 MB
2.6-modern_web_development_with_blazor.mkv 11.4 MB
1.1-our_first_look_at_.net_5.mkv 10.9 MB
2.1-.net_frameworks_versions_and_names.mkv 7.6 MB
1.2-what_you_should_know.mkv 3.4 MB
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【压缩文件】 [ FreeCourseWeb.com ] Udemy - Learning the FOSS4g Stack- Python for Geospatial.zip

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【影视】 [FreeCourseLab.com] Udemy - Learning Algorithms in JavaScript from Scratch

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15. Merge Sort/2. Merge Sort - Code.mp4 17.4 MB
5. Caesar Cipher/2. Caesar Cipher - Code.mp4 17.3 MB
10. Binary Search/2. Introduction to Recursion & the Call Stack.mp4 13.3 MB
3. Harmless Ransom Note/2. Time Complexity & Big O Notation.mp4 13.0 MB
10. Binary Search/3. Binary Search - Code.mp4 12.4 MB
8. Mean Median Mode/3. Mean Median Mode - Code Part 2.mp4 12.0 MB
8. Mean Median Mode/2. Mean Median Mode - Code Part 1.mp4 11.7 MB
16. Max Stock Profit/2. Max Stock Profit - Code.mp4 10.7 MB
4. Is Palindrome/2. Is Palindrome - Code.mp4 10.0 MB
3. Harmless Ransom Note/3. Harmless Ransom Note - Code Part 1.mp4 8.8 MB
13. Sieve of Eratosthenes/2. Sieve of Eratosthenes - Code.mp4 8.8 MB
14. Bubble Sort/1. Bubble Sort - Intro.mp4 8.1 MB
13. Sieve of Eratosthenes/1. Sieve of Eratosthenes - Intro.mp4 7.9 MB
1. Introduction/1. Introduction to Algorithms & Course Layout.mp4 7.8 MB
12. Memoized Fibonacci/2. Memoized Fibonacci - Code.mp4 7.4 MB
14. Bubble Sort/2. Bubble Sort - Code.mp4 7.2 MB
7. Reverse Array In Place/2. Reverse Array In Place - Code.mp4 7.2 MB
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【影视】 [FreeCoursesOnline.Me] [Packt] AWS Lambda and the Serverless Framework - Hands-On Learning! - [FCO]

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00025 Building_the_REST_API.mp4 309.9 MB
00021 Implementation_of_Thumbnail_Service_-_Part_1.mp4 293.2 MB
00005 AWS_Lambda_Console.mp4 268.4 MB
00015 Functions_timeout_and_memory.mp4 245.0 MB
00022 Implementation_of_Thumbnail_Service_-_Part_2.mp4 200.2 MB
00006 Installing_Serverless.mp4 180.5 MB
00018 VPC_for_Lambda_Functions.mp4 168.6 MB
00007 Deploying_our_First_Function.mp4 162.7 MB
00016 IAM_Permissions_for_Lambda_Functions.mp4 162.0 MB
00030 Deploying_the_ec2_start_and_stop_lambda_functions.mp4 134.2 MB
00017 Environment_Variables_in_AWS_Lambda.mp4 128.7 MB
00026 Deploying_the_REST_API.mp4 115.6 MB
00013 Create_AWS_Lambda_function_using_any_runtime.mp4 106.7 MB
00027 Testing_the_REST_API.mp4 105.5 MB
00004 AWS_Lambda_Overview.mp4 102.1 MB
00010 Fetching_the_function_logs_from_the_CLI.mp4 89.4 MB
00009 Updating_the_function_from_the_CLI.mp4 68.4 MB
00014 YAML_Crash_Course.mp4 64.8 MB
00019 AWS_Lambda_Pricing.mp4 50.4 MB
00032 Next_Steps.mp4 35.4 MB

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【其他】 Lynda.Learning.Mailchimp.Aug.2018-XQZT

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【影视】 [Tutorialsplanet.NET] Udemy - Deep Learning Advanced Computer Vision

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9. Appendix FAQ/2. Windows-Focused Environment Setup 2018.mp4 195.4 MB
7. Bonus Class Activation Maps/2. Class Activation Maps (Code).mp4 109.9 MB
8. Basics Review/2. (Review) Tensorflow Neural Network in Code.mp4 102.0 MB
8. Basics Review/1. (Review) Tensorflow Basics.mp4 85.5 MB
9. Appendix FAQ/7. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
8. Basics Review/4. (Review) Keras Neural Network in Code.mp4 69.4 MB
7. Bonus Class Activation Maps/1. Class Activation Maps (Theory).mp4 56.0 MB
9. Appendix FAQ/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.0 MB
9. Appendix FAQ/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.8 MB
8. Basics Review/5. (Review) Keras Functional API.mp4 40.5 MB
3. VGG and Transfer Learning/3. Transfer Learning.mp4 40.0 MB
9. Appendix FAQ/12. What order should I take your courses in (part 2).mp4 39.5 MB
9. Appendix FAQ/12. What order should I take your courses in (part 2).vtt 39.5 MB
9. Appendix FAQ/11. What order should I take your courses in (part 1).mp4 30.7 MB
8. Basics Review/3. (Review) Keras Discussion.mp4 29.0 MB
5. Object Detection (SSD)/8. Modifying SSD to work on Video.vtt 26.0 MB
5. Object Detection (SSD)/8. Modifying SSD to work on Video.mp4 26.0 MB
9. Appendix FAQ/5. How to Code by Yourself (part 1).mp4 25.7 MB
6. Neural Style Transfer/2. Style Transfer Theory.mp4 20.9 MB
2. Review/1. Review of CNNs.vtt 19.4 MB

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【压缩文件】 Complete Data Science & Machine Learning Bootcamp - Python 3.rar

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【影视】 [FreeCourseLab.me] Udemy - Tensorflow 2.0 Deep Learning and Artificial Intelligence

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18. Setting up your Environment/2. Windows-Focused Environment Setup 2018.mp4 203.4 MB
18. Setting up your Environment/3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.mp4 175.4 MB
18. Setting up your Environment/1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 174.8 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/12. Demo of the Long Distance Problem.mp4 150.1 MB
13. Advanced Tensorflow Usage/2. Tensorflow Serving pt 2.mp4 130.5 MB
19. Appendix FAQ/9. What order should I take your courses in (part 2).mp4 128.6 MB
19. Appendix FAQ/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 122.8 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/1. Sequence Data.mp4 108.2 MB
11. Deep Reinforcement Learning (Theory)/2. Elements of a Reinforcement Learning Problem.mp4 102.5 MB
4. Feedforward Artificial Neural Networks/4. Activation Functions.mp4 96.6 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/5. Recurrent Neural Networks.mp4 96.5 MB
5. Convolutional Neural Networks/5. CNN Architecture.mp4 95.4 MB
2. Google Colab/3. Uploading your own data to Google Colab.mp4 93.4 MB
19. Appendix FAQ/8. What order should I take your courses in (part 1).mp4 92.4 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/3. Autoregressive Linear Model for Time Series Prediction.mp4 91.9 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/7. RNN for Time Series Prediction.mp4 91.5 MB
10. GANs (Generative Adversarial Networks)/1. GAN Theory.mp4 90.7 MB
5. Convolutional Neural Networks/11. Improving CIFAR-10 Results.mp4 90.5 MB
5. Convolutional Neural Networks/6. CNN Code Preparation.mp4 90.5 MB
4. Feedforward Artificial Neural Networks/9. ANN for Regression.mp4 88.0 MB

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