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01. Introduction/2.1 FULL_TENSORFLOW_NOTES__AND_DATA.zip.zip 314.2 MB
01. Introduction/3.1 FULL_TENSORFLOW_NOTES__AND_DATA.zip.zip 314.2 MB
06. TensorFlow Basics/8. TensorFlow Regression Example _ Part Two.mp4 60.6 MB
07. Convolutional Neural Networks/13. CNN Project Exercise Solution - Part One.mp4 52.6 MB
10. AutoEncoders/5. Stacked Autoencoder.mp4 46.1 MB
05. Introduction to Neural Networks/11. Manual Neural Network Classification Task.mp4 42.5 MB
09. Miscellaneous Topics/6. Tensorboard.mp4 41.9 MB
10. AutoEncoders/2. Dimensionality Reduction with Linear Autoencoder.mp4 39.4 MB
11. Reinforcement Learning with OpenAI Gym/8. Simple Neural Network Game.mp4 37.6 MB
08. Recurrent Neural Networks/15. Word2Vec Code Along - Part One.mp4 37.3 MB
08. Recurrent Neural Networks/12. Time Series Exercise Solution.mp4 36.8 MB
07. Convolutional Neural Networks/7. MNIST Basic Approach Part Two.mp4 36.6 MB
08. Recurrent Neural Networks/7. RNN with TensorFlow - Part One.mp4 35.7 MB
08. Recurrent Neural Networks/16. Word2Vec Part Two.mp4 35.0 MB
09. Miscellaneous Topics/4. Deep Nets with Tensorflow Abstractions API - Keras.mp4 35.0 MB
11. Reinforcement Learning with OpenAI Gym/11. Policy Gradient Code Along Part Two.mp4 34.4 MB
06. TensorFlow Basics/6. TensorFlow - A Neural Network - Part Two.mp4 34.1 MB
04. Crash Course Overview/2. NumPy Crash Course.mp4 34.1 MB
06. TensorFlow Basics/10. TensorFlow Classification Example - Part Two.mp4 33.5 MB
03. What is Machine Learning/1. Machine Learning Overview.mp4 31.9 MB

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[ DevCourseWeb.com ] PluralSight - Exploring Java Machine Learning Environments.zip 347.7 MB

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[ DevCourseWeb.com ] PluralSight - Exploring Java Machine Learning Environments.zip 347.7 MB

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【压缩文件】 [ FreeCourseWeb.com ] Udemy - Calculus for Data Science & Machine Learning - 2020.zip

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【压缩文件】 [ FreeCourseWeb.com ] Udemy - Machine Learning Prerequisites for 2021.zip

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[ FreeCourseWeb.com ] Udemy - Machine Learning Prerequisites for 2021.zip 485.3 MB

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【压缩文件】 [FreeAllCourse.Com] Udemy - Machine Learning A-Z™ Hands-On Python & R In Data Science

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1. Welcome to the course!/6.1 Machine_Learning_A-Z_New.zip.zip 239.5 MB
36. Kernel PCA/3. Kernel PCA in R.mp4 59.3 MB
1. Welcome to the course!/7. Updates on Udemy Reviews.mp4 55.5 MB
39. XGBoost/5. THANK YOU bonus video.mp4 54.8 MB
12. Logistic Regression/13. Logistic Regression in R - Step 5.mp4 54.2 MB
35. Linear Discriminant Analysis (LDA)/4. LDA in R.mp4 53.8 MB
17. Decision Tree Classification/4. Decision Tree Classification in R.mp4 53.7 MB
18. Random Forest Classification/4. Random Forest Classification in R.mp4 51.8 MB
31. Artificial Neural Networks/13. ANN in Python - Step 2.mp4 50.4 MB
39. XGBoost/4. XGBoost in R.mp4 49.6 MB
27. Upper Confidence Bound (UCB)/10. Upper Confidence Bound in R - Step 3.mp4 49.5 MB
18. Random Forest Classification/3. Random Forest Classification in Python.mp4 49.5 MB
32. Convolutional Neural Networks/20. CNN in Python - Step 9.mp4 49.1 MB
7. Support Vector Regression (SVR)/2. SVR Intuition.mp4 48.9 MB
7. Support Vector Regression (SVR)/3. SVR in Python.mp4 48.4 MB
35. Linear Discriminant Analysis (LDA)/3. LDA in Python.mp4 47.6 MB
8. Decision Tree Regression/4. Decision Tree Regression in R.mp4 46.5 MB
16. Naive Bayes/1. Bayes Theorem.mp4 46.0 MB
24. Apriori/5. Apriori in R - Step 3.mp4 46.0 MB
38. Model Selection/3. k-Fold Cross Validation in R.mp4 45.8 MB