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~Get Your Files Here !/8. Linear Regression With Python/5. Linear Regression With Python.mp4 149.7 MB
~Get Your Files Here !/9. Logistic Regression With Python/5. Logistic Regression With Python.mp4 110.0 MB
~Get Your Files Here !/14. Discriminant Analysis With A Case Study/1. Discriminant Analysis - Lecture 1.mp4 106.7 MB
~Get Your Files Here !/17. Deep Learning/2. Introduction To Artificial Neural Networks (ANNs).mp4 74.8 MB
~Get Your Files Here !/15. Support Vector Machines With Python/2. Support Vector Machines - Lecture 2.mp4 74.1 MB
~Get Your Files Here !/5. The NumPy Library/2. Working With Arrays Using NumPy Library.mp4 69.9 MB
~Get Your Files Here !/17. Deep Learning/5. ANN With Back Propagation.mp4 68.3 MB
~Get Your Files Here !/17. Deep Learning/4. Perceptron With Python.mp4 65.4 MB
~Get Your Files Here !/12. Naïve Bayes Classifier And KNN/1. Understanding Naïve Bayes Classifier.mp4 65.4 MB
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~Get Your Files Here !/17. Deep Learning/3. Architecture And Training Of ANN.mp4 64.7 MB
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~Get Your Files Here !/15. Support Vector Machines With Python/4. SVM With Python.mp4 63.2 MB
~Get Your Files Here !/14. Discriminant Analysis With A Case Study/2. Discriminant Analysis - Lecture 2.mp4 59.9 MB
~Get Your Files Here !/7. Data Visualization With Python/3. Data Analysis And Visualization.mp4 52.3 MB
~Get Your Files Here !/10. Complete Decision Tree With Python/7. Decision Tree Hands-on With Python - Lecture 2.mp4 51.2 MB
~Get Your Files Here !/15. Support Vector Machines With Python/3. Support Vector Machines - Lecture 3.mp4 50.9 MB
~Get Your Files Here !/13. Random Forest With Python/1. Ensemble Classifiers- Random Forest - Lecture 1.mp4 49.1 MB
~Get Your Files Here !/10. Complete Decision Tree With Python/1. Fundamentals Of Decision Tree - Lecture 1.mp4 48.8 MB
~Get Your Files Here !/13. Random Forest With Python/3. Random Forest Classifier In Python - Lecture 1.mp4 48.7 MB

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9. Appendix/3. Windows-Focused Environment Setup 2018.mp4 195.4 MB
3. Naive Bayes and Bayes Classifiers/1. Bayes Classifier Intuition (Continuous).mp4 84.1 MB
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3. Naive Bayes and Bayes Classifiers/2. Bayes Classifier Intuition (Discrete).mp4 52.5 MB
9. Appendix/4. How to install Numpy, Scipy, Matplotlib, and Sci-Kit Learn.mp4 46.0 MB
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9. Appendix/12. What order should I take your courses in (part 2).mp4 39.4 MB
2. K-Nearest Neighbor/7. Effect of K.mp4 37.5 MB
4. Decision Trees/6. Decision Tree in Code.mp4 31.8 MB
9. Appendix/11. What order should I take your courses in (part 1).mp4 30.7 MB
9. Appendix/5. How to Code by Yourself (part 1).mp4 25.7 MB
4. Decision Trees/1. Decision Tree Intuition.mp4 21.4 MB
2. K-Nearest Neighbor/3. KNN in Code with MNIST.mp4 18.8 MB
2. K-Nearest Neighbor/1. K-Nearest Neighbor Intuition.mp4 18.4 MB
6. Practical Machine Learning/5. Sci-Kit Learn.mp4 16.6 MB
3. Naive Bayes and Bayes Classifiers/3. Naive Bayes.mp4 16.5 MB
9. Appendix/6. How to Code by Yourself (part 2).mp4 15.5 MB
3. Naive Bayes and Bayes Classifiers/5. Naive Bayes in Code with MNIST.mp4 15.1 MB
4. Decision Trees/4. Maximizing Information Gain.mp4 14.6 MB
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【影视】 [ FreeCourseWeb.com ] Udemy - Unleashing Unlabelled Data - Self-Supervised Learning

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~Get Your Files Here !/4. Miscellaneous Concepts/4. Introduction To Convolutional Neural Networks (CNN).mp4 184.5 MB
~Get Your Files Here !/4. Miscellaneous Concepts/2. Theory Behind ANN and DNN.mp4 101.9 MB
~Get Your Files Here !/4. Miscellaneous Concepts/3. What Are Activation Functions.mp4 91.7 MB
~Get Your Files Here !/2. Basic Data Preprocessing/2. What Is Pandas.mp4 78.5 MB
~Get Your Files Here !/2. Basic Data Preprocessing/4. Basics of Data Visualisation.mp4 77.5 MB
~Get Your Files Here !/4. Miscellaneous Concepts/1. What is Supervised Learning.mp4 76.0 MB
~Get Your Files Here !/3. Learning From Unlabelled Data/9. Autoencoders With Keras Deep Learning.mp4 71.6 MB
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~Get Your Files Here !/3. Learning From Unlabelled Data/2. Theory Behind Autoencoders.mp4 63.4 MB
~Get Your Files Here !/3. Learning From Unlabelled Data/4. Lets Implement a Basic Auto-Encoder With H20.mp4 61.1 MB
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~Get Your Files Here !/3. Learning From Unlabelled Data/6. What Is Denoising.mp4 49.4 MB
~Get Your Files Here !/1. Introduction To the Course/3. Python Installation.mp4 44.7 MB
~Get Your Files Here !/1. Introduction To the Course/4. Start With Google Colaboratory Environment.mp4 42.3 MB
~Get Your Files Here !/3. Learning From Unlabelled Data/7. Autoencode the Image Data With H2O.mp4 41.4 MB
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~Get Your Files Here !/3. Learning From Unlabelled Data/5. Variational Autoencoder (VAE) With H2O.mp4 38.4 MB
~Get Your Files Here !/2. Basic Data Preprocessing/3. Basic Data Cleaning With Pandas.mp4 36.1 MB
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01 Introduction and Review/001 Introduction and Outline.mp4 8.0 MB
01 Introduction and Review/002 Review of Important Concepts.mp4 6.3 MB
01 Introduction and Review/003 Where to get the Code and Data.mp4 4.0 MB
01 Introduction and Review/004 How to Succeed in this Course.mp4 9.2 MB
02 K-Nearest Neighbor/005 K-Nearest Neighbor Concepts.mp4 9.0 MB
02 K-Nearest Neighbor/006 KNN in Code with MNIST.mp4 18.8 MB
02 K-Nearest Neighbor/007 When KNN Can Fail.mp4 8.1 MB
02 K-Nearest Neighbor/008 KNN for the XOR Problem.mp4 4.5 MB
02 K-Nearest Neighbor/009 KNN for the Donut Problem.mp4 5.7 MB
03 Naive Bayes and Bayes Classifiers/010 Naive Bayes.mp4 16.5 MB
03 Naive Bayes and Bayes Classifiers/011 Naive Bayes Handwritten Example.mp4 6.1 MB
03 Naive Bayes and Bayes Classifiers/012 Naive Bayes in Code with MNIST.mp4 15.1 MB
03 Naive Bayes and Bayes Classifiers/013 Non-Naive Bayes.mp4 7.7 MB
03 Naive Bayes and Bayes Classifiers/014 Bayes Classifier in Code with MNIST.mp4 4.7 MB
03 Naive Bayes and Bayes Classifiers/015 Linear Discriminant Analysis LDA and Quadratic Discriminant Analysis QDA.mp4 10.9 MB
03 Naive Bayes and Bayes Classifiers/016 Generative vs Discriminative Models.mp4 5.4 MB
04 Decision Trees/017 Decision Tree Basics.mp4 8.7 MB
04 Decision Trees/018 Information Entropy.mp4 7.3 MB
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09 Appendix/035 How to install Numpy Scipy Matplotlib and Sci-Kit Learn.mp4 46.0 MB
04 Decision Trees/021 Decision Tree in Code.mp4 31.8 MB
09 Appendix/036 How to Code by Yourself part 1.mp4 25.7 MB
02 K-Nearest Neighbor/006 KNN in Code with MNIST.mp4 18.8 MB
06 Practical Machine Learning/030 Sci-Kit Learn.mp4 16.6 MB
03 Naive Bayes and Bayes Classifiers/010 Naive Bayes.mp4 16.5 MB
09 Appendix/037 How to Code by Yourself part 2.mp4 15.5 MB
03 Naive Bayes and Bayes Classifiers/012 Naive Bayes in Code with MNIST.mp4 15.1 MB
04 Decision Trees/019 Maximizing Information Gain.mp4 14.6 MB
05 Perceptrons/023 Perceptron in Code.mp4 14.4 MB
05 Perceptrons/022 Perceptron Concepts.mp4 12.8 MB
07 Building a Machine Learning Web Service/033 Building a Machine Learning Web Service Code.mp4 12.4 MB
06 Practical Machine Learning/031 Regression with Sci-Kit Learn is Easy.mp4 11.3 MB
03 Naive Bayes and Bayes Classifiers/015 Linear Discriminant Analysis LDA and Quadratic Discriminant Analysis QDA.mp4 10.9 MB
01 Introduction and Review/004 How to Succeed in this Course.mp4 9.2 MB
05 Perceptrons/024 Perceptron for MNIST and XOR.mp4 9.2 MB
06 Practical Machine Learning/028 Comparison to Deep Learning.mp4 9.1 MB
02 K-Nearest Neighbor/005 K-Nearest Neighbor Concepts.mp4 9.0 MB
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