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Practical Machine Learning with TensorFlow 2.0 and Scikit-Learn

You're reading from Practical Machine Learning with TensorFlow 2.0 and Scikit-Learn Build effective models in scikit-learn with TensorFlow 2.0

Product type Video

Published in Jun 2020

Publisher Packt

ISBN-13 9781789959161

Length 10hrs 28mins

Edition 1st Edition

Languages

Python

Tools

Scikit-learn

Concepts

Machine Learning

Author (1):

Samuel Holt

View More author details

Table of Contents (9) Chapters

Installing Scikit-Learn and TensorFlow 2.0

ML Fundamentals: Scikit-Learn Introduction FREE CHAPTER

Applied Scikit-Learn: Supervised Learning Models

Unsupervised Learning

TensorFlow 2.0 Essentials for ML

Applied Deep Learning for Computer Vision Tasks

Natural Language Processing and Sequential Data

Applied Sequence to Sequence and Transformer Models

Working with Reinforcement Learning

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Authors (1)

Samuel Holt

Samuel Holt

Samuel Holt has several years' experience implementing, creating, and putting into production machine learning models for large blue-chip companies and small startups (as well as within his own companies) as a machine learning consultant. He has machine learning lab experience and holds an MEng in Machine Learning and Software Engineering from Oxford University, where he won four awards for academic excellence. Specifically, he has built systems that run in production using a combination of scikit-learn and TensorFlow involving automated customer support, implementing document OCR, detecting vehicles in the case of self-driving cars, comment analysis, and time series forecasting for financial data.

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