Python 3 for Machine Learning – PDF

The ebook Python 3 for Machine Learning (PDF) is designed to supply the reader fundamental Python3 programming ideas related to machine studying. The first 4 chapters supply a quick-paced introduction to NumPy, Python 3, and Pandas. The fifth chapter presents the elemental ideas of machine studying. The sixth chapter is devoted to machine studying classifiers, like logistic regression, okay-NN, random forests, resolution bushes, and SVMs. The ultimate chapter options materials on NLP and RL. Keras-based code samples are included to enhance the theoretical dialogue. The ebook additionally consists of separate appendices for common expressions, Keras, and TensorFlow 2. C Features

• Presents separate appendices for common expressions, Keras, and TensorFlow 2
• Offers the reader with fundamental Python 3 programming ideas associated to machine studying

Brief Table of Contents 1: Introduction to Python 3. 2: Conditional Logic, Loops, and Functions. 3: Python Collections. 4: Introduction to NumPy and Pandas. 5: Introduction to Machine Learning. 6: (*3*) in Machine Learning. 7: Natural Language Processing and Reinforcement Learning. Appendices. A: Introduction to Regular Expressions. B: Introduction to Keras. C: Introduction to TensorFlow 2. Index. NOTE: The product only consists of the ebook, Python 3 for Machine Learning in PDF. No access codes, samples, or coding recordsdata are included.