[FreeCoursesOnline.Us] Machine-Learning-Essential-Training-Value-Estimations

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文档列表

05 Coding Our System/003 Train the value estimator.mp4 9.3 MB
04 Features/002 Choose the best features for home value prediction.mp4 9.3 MB
03 Training Data/001 Explore a home value data set.mp4 8.7 MB
07 Using the Estimator in a Real-World Program/001 Predict values for new data.mp4 8.0 MB
01 What Is Machine Learning and Value Prediction_/003 Build a simple home value estimator.mp4 7.4 MB
04 Features/001 Feature engineering.mp4 7.3 MB
00 Introduction/004 Set up the development environment.mp4 7.2 MB
06 Improving Our System/003 Feature selection.mp4 7.2 MB
01 What Is Machine Learning and Value Prediction_/004 Find the best weights automatically.mp4 7.2 MB
00 Introduction/001 Welcome.mp4 7.1 MB
01 What Is Machine Learning and Value Prediction_/005 Cool uses of value prediction.mp4 7.0 MB
02 An Overview of Building a Machine Learning System/004 Gradient boosting_ A versatile machine learning algorithm.mp4 6.4 MB
06 Improving Our System/002 The brute force solution_ Grid search.mp4 6.4 MB
02 An Overview of Building a Machine Learning System/002 Think in vectors_ How to work with large data sets efficiently.mp4 5.9 MB
01 What Is Machine Learning and Value Prediction_/002 Supervised machine learning for value prediction.mp4 5.5 MB
05 Coding Our System/001 Prepare the features.mp4 5.2 MB
01 What Is Machine Learning and Value Prediction_/001 What is machine learning_.mp4 4.8 MB
06 Improving Our System/001 Overfitting and underfitting.mp4 4.7 MB
05 Coding Our System/004 Measure accuracy with mean absolute error.mp4 4.7 MB
03 Training Data/003 Decide how much data you need.mp4 4.0 MB
02 An Overview of Building a Machine Learning System/003 The basic workflow for training a supervised machine learning model.mp4 3.9 MB
07 Using the Estimator in a Real-World Program/002 Retrain the classifier with fresh data.mp4 3.8 MB
04 Features/003 Use as few features as possible_ The curse of dimensionality.mp4 3.3 MB
05 Coding Our System/002 Training vs. testing data.mp4 3.1 MB
02 An Overview of Building a Machine Learning System/001 Introduction to NumPy, scikit-learn, and pandas.mp4 2.2 MB
03 Training Data/002 Standard conventions for naming training data.mp4 1.6 MB
08 Conclusion/001 Wrap-up.mp4 1.5 MB
00 Introduction/003 Using the exercise files.mp4 1.3 MB
00 Introduction/002 What you should know.mp4 634.4 kB
04 Features/001 Feature engineering.srt 10.2 kB
01 What Is Machine Learning and Value Prediction_/004 Find the best weights automatically.srt 10.1 kB
01 What Is Machine Learning and Value Prediction_/001 What is machine learning_.srt 9.2 kB
02 An Overview of Building a Machine Learning System/004 Gradient boosting_ A versatile machine learning algorithm.srt 9.0 kB
04 Features/002 Choose the best features for home value prediction.srt 8.1 kB
03 Training Data/001 Explore a home value data set.srt 7.0 kB
01 What Is Machine Learning and Value Prediction_/002 Supervised machine learning for value prediction.srt 6.8 kB
06 Improving Our System/001 Overfitting and underfitting.srt 6.5 kB
02 An Overview of Building a Machine Learning System/002 Think in vectors_ How to work with large data sets efficiently.srt 6.5 kB
06 Improving Our System/002 The brute force solution_ Grid search.srt 6.3 kB
05 Coding Our System/003 Train the value estimator.srt 6.2 kB
01 What Is Machine Learning and Value Prediction_/003 Build a simple home value estimator.srt 6.1 kB
07 Using the Estimator in a Real-World Program/001 Predict values for new data.srt 5.7 kB
06 Improving Our System/003 Feature selection.srt 5.7 kB
02 An Overview of Building a Machine Learning System/003 The basic workflow for training a supervised machine learning model.srt 5.6 kB
00 Introduction/004 Set up the development environment.srt 5.2 kB
01 What Is Machine Learning and Value Prediction_/005 Cool uses of value prediction.srt 5.1 kB
03 Training Data/003 Decide how much data you need.srt 4.5 kB
04 Features/003 Use as few features as possible_ The curse of dimensionality.srt 4.3 kB
07 Using the Estimator in a Real-World Program/002 Retrain the classifier with fresh data.srt 3.9 kB
05 Coding Our System/001 Prepare the features.srt 3.5 kB
02 An Overview of Building a Machine Learning System/001 Introduction to NumPy, scikit-learn, and pandas.srt 3.2 kB
05 Coding Our System/004 Measure accuracy with mean absolute error.srt 3.1 kB
05 Coding Our System/002 Training vs. testing data.srt 2.3 kB
08 Conclusion/001 Wrap-up.srt 1.9 kB
03 Training Data/002 Standard conventions for naming training data.srt 1.8 kB
00 Introduction/001 Welcome.srt 1.7 kB
00 Introduction/003 Using the exercise files.srt 1.3 kB
00 Introduction/002 What you should know.srt 863 Bytes
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[FreeCoursesOnline.Us].url 123 Bytes
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