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5. Data Science Environment Setup/8. Windows Environment Setup 2.mp4 238.7 MB
9. Scikit-learn Creating Machine Learning Models/7. Typical scikit-learn Workflow.mp4 199.4 MB
9. Scikit-learn Creating Machine Learning Models/8. Optional Debugging Warnings In Jupyter.mp4 184.7 MB
16. Career Advice + Extra Bits/9. CWD Git + Github.mp4 184.7 MB
9. Scikit-learn Creating Machine Learning Models/41. Tuning Hyperparameters.mp4 184.3 MB
14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/32. Training Your Deep Neural Network.mp4 174.7 MB
16. Career Advice + Extra Bits/3. What If I Don't Have Enough Experience.mp4 168.8 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/8. Feature Engineering.mp4 166.9 MB
14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/34. Make And Transform Predictions.mp4 162.5 MB
9. Scikit-learn Creating Machine Learning Models/48. Putting It All Together.mp4 157.9 MB
14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/21. Turning Data Into Batches 2.mp4 156.7 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/9. Turning Data Into Numbers.mp4 153.3 MB
5. Data Science Environment Setup/5. Mac Environment Setup.mp4 151.4 MB
14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/37. Visualizing And Evaluate Model Predictions 2.mp4 150.8 MB
9. Scikit-learn Creating Machine Learning Models/16. Choosing The Right Model For Your Data.mp4 150.2 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/21. Feature Importance.mp4 149.2 MB
14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/41. Making Predictions On Test Images.mp4 147.7 MB
14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/40. Training Model On Full Dataset.mp4 146.6 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/19. Preproccessing Our Data.mp4 146.1 MB
11. Milestone Project 1 Supervised Learning (Classification)/10. Finding Patterns 3.mp4 144.6 MB

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【影视】 [FreeCourseLab.com] Udemy - A-Z Machine Learning using Azure Machine Learning (AzureML)

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7. Regression Analysis/3. [Hands On] - Linear Regression model using OLS.mp4 95.5 MB
12. Text Analytics and Natural Language Processing/5. [Hands On] - Classify Customer Complaints using Text Analytics.mp4 95.4 MB
12. Text Analytics and Natural Language Processing/4. Feature Hashing.mp4 78.8 MB
1. Basics of Machine Learning/4. Why Machine Learning is the Future.mp4 72.1 MB
10. Feature Selection - Select a subset of Variables or features with highest impact/9. [Hands On] - Fisher Based LDA - Experiment.mp4 64.1 MB
13. Thank You and Bonus Lecture/1. Way Forward.mp4 59.8 MB
12. Text Analytics and Natural Language Processing/2. Text Pre-Processing.mp4 57.3 MB
4. Classification/2. [Hands On] -Logistic Regression - Build Two-Class Loan Approval Prediction Model.mp4 54.7 MB
12. Text Analytics and Natural Language Processing/3. Bag Of Words and N-Gram Models for Text features.mp4 52.4 MB
10. Feature Selection - Select a subset of Variables or features with highest impact/2. Pearson Correlation Coefficient.mp4 49.5 MB
12. Text Analytics and Natural Language Processing/1. What is Text Analytics or Natural Language Processing.mp4 42.7 MB
3. Data Processing/5. [Hands On] - Apply SQL Transformation, Clean Missing Data, Edit Metadata.mp4 40.8 MB
11. Recommendation System/5. [Hands On] - Restaurant Recommendation Experiment.mp4 37.9 MB
3. Data Processing/6. [Hands On] - Sample and Split Data - Partition or Sample, Train and Test Data.mp4 37.2 MB
4. Classification/12. [Hands On] - Two Class Decision Forest - Adult Census Income Prediction.mp4 36.8 MB
11. Recommendation System/1. What is a Recommendation System.mp4 36.7 MB
8. Clustering/2. [Hands On] - Cluster Analysis Experiment 1.mp4 32.4 MB
4. Classification/4. Understanding the Confusion Matrix, AUC, Accuracy, Precision, Recall and F1Score.mp4 30.9 MB
7. Regression Analysis/5. Gradient Descent.mp4 29.0 MB
3. Data Processing/4. [Hands On] -Data Transform - Add RowsColumns, Remove Duplicates, Select Columns.mp4 27.8 MB

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【影视】 [FreeCourseLab.com] Udemy - A Beginner's Guide To Machine Learning with Unity

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1. Introduction/6. Machine Learning 101.mp4 580.1 MB
10. A Final Word/2. Where to Now.mp4 262.9 MB
8. Unity's ML-Agents V0.3 [DEPRECATED]/2. Training Your First ML-Agent V0.3.mp4 180.6 MB
8. Unity's ML-Agents V0.3 [DEPRECATED]/8.2 CatAcademy.zip.zip 142.6 MB
2. Genetic Algorithms/1. DNA Inspired Data Structures.mp4 114.4 MB
2. Genetic Algorithms/10. Moving GAs with Senses Part 2.mp4 79.2 MB
2. Genetic Algorithms/11. Moving GAs with Senses Part 3.mp4 72.1 MB
5. Neural Networks in Practice/6. Gathering Training Data from the Player Part 2.mp4 69.0 MB
5. Neural Networks in Practice/5. Gathering Training Data from the Player Part 1.mp4 63.0 MB
8. Unity's ML-Agents V0.3 [DEPRECATED]/15. Goal Seeking Wall Jumping Part 2.mp4 62.6 MB
2. Genetic Algorithms/6. Coding Movement with Genes Part 2.mp4 60.5 MB
5. Neural Networks in Practice/9. Training with Player Data Part 2.mp4 54.3 MB
2. Genetic Algorithms/12. Maze Walking Challenge.mp4 52.6 MB
4. Artificial Neural Networks/3. Programming An Artificial Neural Network Part 2.mp4 51.5 MB
4. Artificial Neural Networks/5. ANN FAQs.mp4 50.3 MB
8. Unity's ML-Agents V0.3 [DEPRECATED]/5. Creating an ML-Agent From Scratch Part 1.mp4 50.1 MB
5. Neural Networks in Practice/10. Training with Player Data Part 3.mp4 49.9 MB
3. Perceptrons The making of a Neural Network/6. Perceptron Classification.mp4 48.8 MB
5. Neural Networks in Practice/7. Training with Player Data Part 1.mp4 47.5 MB
2. Genetic Algorithms/9. Moving GAs with Senses Part 1.mp4 46.7 MB

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【影视】 [FreeCourseLab.me] Udemy - Ensemble Machine Learning in Python Random Forest, AdaBoost

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6. Appendix FAQ/3. Windows-Focused Environment Setup 2018.mp4 195.3 MB
6. Appendix FAQ/9. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
3. Bootstrap Estimates and Bagging/1. Bootstrap Estimation.mp4 50.0 MB
6. Appendix FAQ/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.1 MB
2. Bias-Variance Trade-Off/4. Polynomial Regression Demo.mp4 43.8 MB
6. Appendix FAQ/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.8 MB
6. Appendix FAQ/13. BONUS Where to get Udemy coupons and FREE deep learning material.srt 39.7 MB
6. Appendix FAQ/13. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 39.7 MB
6. Appendix FAQ/12. What order should I take your courses in (part 2).mp4 39.5 MB
3. Bootstrap Estimates and Bagging/1. Bootstrap Estimation.srt 31.5 MB
6. Appendix FAQ/11. What order should I take your courses in (part 1).mp4 30.8 MB
6. Appendix FAQ/5. How to Code by Yourself (part 1).mp4 25.7 MB
3. Bootstrap Estimates and Bagging/5. Bagging Classification Trees.mp4 21.3 MB
4. Random Forest/6. Connection to Deep Learning Dropout.srt 19.9 MB
5. AdaBoost/4. AdaBoost Implementation.srt 19.4 MB
4. Random Forest/1. Random Forest Algorithm.srt 17.7 MB
3. Bootstrap Estimates and Bagging/4. Bagging Regression Trees.mp4 16.6 MB
5. AdaBoost/4. AdaBoost Implementation.mp4 16.5 MB
4. Random Forest/2. Random Forest Regressor.mp4 15.6 MB
6. Appendix FAQ/6. How to Code by Yourself (part 2).mp4 15.5 MB

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