Thoroughly updated using the latest Python open source libraries, Python Machine Learning – Second Edition offers the practical knowledge and techniques you need to create and contribute to machine learning, deep learning, and modern data analysis. (Limited-time offer)
Table of Contents
- Giving Computers the Ability to Learn from Data
- Training Simple Machine Learning Algorithms for Classification
- A Tour of Machine Learning Classifiers Using scikit-learn
- Building Good Training Sets – Data Preprocessing
- Compressing Data via Dimensionality Reduction
- Learning Best Practices for Model Evaluation and Hyperparameter Tuning
- Combining Different Models for Ensemble Learning
- Applying Machine Learning to Sentiment Analysis
- Embedding a Machine Learning Model into a Web Application
- Predicting Continuous Target Variables with Regression Analysis
- Working with Unlabeled Data – Clustering Analysis
- Implementing a Multilayer Artificial Neural Network from Scratch
- Parallelizing Neural Network Training with TensorFlow
- Going Deeper – The Mechanics of TensorFlow
- Classifying Images with Deep Convolutional Neural Networks
- Modeling Sequential Data Using Recurrent Neural Networks
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Author(s): Sebastian Raschka , Vahid Mirjalili
Publisher: Packt Publishing
Published: September 2017
Format(s): Online
File size: –
Number of pages: 622
Download / View Link(s): This offer has ended.
Free as of03/30/2021 12/06/2021 11/10/2022
Publisher: Packt Publishing
Published: September 2017
Format(s): Online
File size: –
Number of pages: 622
Download / View Link(s): This offer has ended.
Free as of