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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/39. Tuning Hyperparameters.mp4 184.1 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)/7. Feature Engineering.mp4 166.9 MB
9. Scikit-learn Creating Machine Learning Models/45. Putting It All Together.mp4 166.1 MB
14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/34. Make And Transform Predictions.mp4 162.5 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)/8. 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/15. Choosing The Right Model For Your Data.mp4 150.2 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/20. 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)/18. Preproccessing Our Data.mp4 146.1 MB
11. Milestone Project 1 Supervised Learning (Classification)/9. Finding Patterns 3.mp4 144.6 MB

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【影视】 [FreeCourseLab.com] Udemy - 2019 AWS SageMaker and Machine Learning - With Python

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10. 2019 SageMaker HyperParameter Tuning/3. Lab Tuning Movie Rating Factorization Machine Recommender System.mp4 161.5 MB
5. XGBoost - Gradient Boosted Trees/10. Demo - Training on SageMaker Cloud - Kaggle Bike Rental Model Version 3.mp4 133.4 MB
8. SageMaker - DeepAR Time Series Forecasting/5. Demo - Bike Rental as Time Series Forecasting Problem.mp4 110.1 MB
3. 2019 Machine Learning Concepts/2. 2019 Data Types - How to handle mixed data types.mp4 107.2 MB
5. XGBoost - Gradient Boosted Trees/4. Demo - Working with XGBoost - Linear Regression Straight Line Fit.mp4 104.5 MB
5. XGBoost - Gradient Boosted Trees/6. Demo - Kaggle Bike Rental Data Setup, Exploration and Preparation.mp4 101.8 MB
5. XGBoost - Gradient Boosted Trees/7. Demo - Kaggle Bike Rental Model Version 1.mp4 100.8 MB
7. SageMaker - Factorization Machines/4. Demo - Movie Recommender Data Preparation.mp4 95.1 MB
8. SageMaker - DeepAR Time Series Forecasting/3. DeepAR Training and Inference Formats.mp4 93.8 MB
3. 2019 Machine Learning Concepts/3. 2019 Introduction to Python Notebook Environment.mp4 89.7 MB
9. 2019 Integration Options - Model Endpoint/9. Microservice - API Gateway, Lambda to Endpoint.mp4 88.2 MB
5. XGBoost - Gradient Boosted Trees/16. Demo - XGBoost Multi-Class Classification Iris Data.mp4 85.8 MB
3. 2019 Machine Learning Concepts/4. 2019 Introduction to working with Missing Data.mp4 85.7 MB
8. SageMaker - DeepAR Time Series Forecasting/6. Demo - Bike Rental Model Training.mp4 81.0 MB
9. 2019 Integration Options - Model Endpoint/5. Client to Endpoint using SageMaker SDK.mp4 80.7 MB
8. SageMaker - DeepAR Time Series Forecasting/2. Introduction to DeepAR Time Series Forecasting.mp4 79.5 MB
9. 2019 Integration Options - Model Endpoint/8. Microservice - Lambda to Endpoint.mp4 77.8 MB
5. XGBoost - Gradient Boosted Trees/1. Introduction to XGBoost.mp4 76.1 MB
3. 2019 Machine Learning Concepts/1. 2019 Introduction to Machine Learning, Concepts, Terminologies.mp4 73.6 MB
7. SageMaker - Factorization Machines/6. Demo - Movie Predictions By User.mp4 72.3 MB

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【影视】 [FreeCoursesOnline.Me] [Packt] Machine Learning for Algorithmic Trading Bots with Python [FCO]

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05.Build Advanced Trading Algorithm/0502.Implement Scalpers Trading Strategy.mp4 127.9 MB
Exercise Files/exercise_files.zip 94.4 MB
01.Building Your First Trading Bot/0105.Fetching and Understanding the Dataset.mp4 71.6 MB
03.Build a Trading Algorithm/0303.Implement Exploit Correlation Strategy.mp4 60.7 MB
02.Design a Machine Learning Model/0202.Build and Implement Random Forests Algorithm.mp4 54.3 MB
06.Model and Strategy Evaluation/0601.Introducing Value at Risk Backtest.mp4 42.4 MB
01.Building Your First Trading Bot/0101.The Course Overview.mp4 42.0 MB
06.Model and Strategy Evaluation/0605.Conclusion and Next steps..mp4 41.2 MB
04.Design Advanced Machine Learning Model/0402.Implementing GBoosting Using Python.mp4 38.7 MB
06.Model and Strategy Evaluation/0604.Implement VaR Using SVR.mp4 38.7 MB
06.Model and Strategy Evaluation/0602.Implement Value at Risk Backtest.mp4 37.1 MB
01.Building Your First Trading Bot/0107.Evaluate the Strategy’s Performance.mp4 36.9 MB
04.Design Advanced Machine Learning Model/0403.Evaluating the Model Performance.mp4 36.0 MB
02.Design a Machine Learning Model/0201.Intuition behind Random Forests Algorithm.mp4 34.7 MB
01.Building Your First Trading Bot/0102.Introduction to Financial Machine Learning and Algorithmic Trading.mp4 32.8 MB
01.Building Your First Trading Bot/0103.Setting up the Environment.mp4 30.2 MB
01.Building Your First Trading Bot/0106.Build the Conventional Buy and Hold Strategy.mp4 26.0 MB
05.Build Advanced Trading Algorithm/0503.Evaluate Scalpers Trading Strategy.mp4 25.8 MB
02.Design a Machine Learning Model/0203.Plug-in Random Forests Implementation into Your Bot.mp4 22.6 MB
01.Building Your First Trading Bot/0104.Project Skeleton Overview.mp4 22.0 MB

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

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25. Neural Nets and Deep Learning/31. Tensorboard.mp4 151.2 MB
25. Neural Nets and Deep Learning/24. Keras Project Solutions - Dealing with Missing Data.mp4 150.6 MB
25. Neural Nets and Deep Learning/16. TF Regression Code Along - Exploratory Data Analysis.mp4 143.6 MB
25. Neural Nets and Deep Learning/27. Keras Project Solutions - Data PreProcessing.mp4 131.0 MB
25. Neural Nets and Deep Learning/21. TF Classification - Dealing with Overfitting and Evaluation.mp4 116.7 MB
25. Neural Nets and Deep Learning/25. Keras Project Solutions - Dealing with Missing Data - Part Two.mp4 101.5 MB
26. Big Data and Spark with Python/7. EC2 Instance Set-Up.mp4 90.7 MB
25. Neural Nets and Deep Learning/26. Keras Project Solutions - Categorical Data.mp4 89.5 MB
25. Neural Nets and Deep Learning/14. TF Syntax Basics - Part Two - Creating and Training the Model.mp4 88.4 MB
14. Introduction to Machine Learning/4. Evaluating Performance - Classification Error Metrics.mp4 86.7 MB
25. Neural Nets and Deep Learning/23. TensorFlow 2.0 Project Notebook Overview.mp4 84.4 MB
2. Environment Set-Up/1. Python Environment Setup.mp4 80.1 MB
25. Neural Nets and Deep Learning/17. TF Regression Code Along - Exploratory Data Analysis - Continued.mp4 79.9 MB
25. Neural Nets and Deep Learning/10. Cost Functions and Gradient Descent.mp4 79.7 MB
18. K Nearest Neighbors/4. KNN Project Solutions.mp4 74.3 MB
26. Big Data and Spark with Python/12. RDD Transformations and Actions.mp4 74.2 MB
26. Big Data and Spark with Python/9. PySpark Setup.mp4 74.1 MB
25. Neural Nets and Deep Learning/19. TF Regression Code Along - Model Evaluation and Predictions.mp4 72.3 MB
25. Neural Nets and Deep Learning/15. TF Syntax Basics - Part Three - Model Evaluation.mp4 67.9 MB
25. Neural Nets and Deep Learning/30. Keras Project Solutions - Model Evaluation.mp4 66.2 MB

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