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Python Machine Learning
Table of Contents
- Giving Computers the Ability to Learn from Data
- Training Simple ML Algorithms for Classification
- ML Classifiers Using scikit-learn
- Building Good Training Datasets - Data Preprocessing
- Compressing Data via Dimensionality Reduction
- Best Practices for Model Evaluation and Hyperparameter Tuning
- Combining Different Models for Ensemble Learning
- Applying ML to Sentiment Analysis
- Embedding a ML Model into a Web Application
- Predicting Continuous Target Variables with Regression Analysis
- Working with Unlabeled Data - Clustering Analysis
- Implementing Multilayer Artificial Neural Networks
- Parallelizing Neural Network Training with TensorFlow
- TensorFlow Mechanics
- Classifying Images with Deep Convolutional Neural Networks
- Modeling Sequential Data Using Recurrent Neural Networks
- GANs for Synthesizing New Data
- RL for Decision Making in Complex Environments
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