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This is the code repository for Mastering Predictive Analytics with scikit-learn and TensorFlow, published by Packt.
Implement machine learning techniques to build advanced predictive models using Python
Python is a programming language that provides a wide range of features that can be used in the field of data science. Mastering Predictive Analytics with scikit-learn and TensorFlow covers various implementations of ensemble methods, how they are used with real-world datasets, and how they improve prediction accuracy in classification and regression problems.
This book covers the following exciting features: Use ensemble algorithms to obtain accurate predictions Apply dimensionality reduction techniques to combine features and build better models Choose the optimal hyperparameters using cross-validation Implement different techniques to solve current challenges in the predictive analytics domain Understand various elements of deep neural network (DNN) models Implement neural networks to solve both classification and regression problems
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All of the code is organized into folders. For example, Chapter02.
The code will look like the following:
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
%matplotlib inline
Following is what you need for this book: Mastering Predictive Analytics with scikit-learn and TensorFlow is for data analysts, software engineers, and machine learning developers who are interested in implementing advanced predictive analytics using Python. Business intelligence experts will also find this book indispensable as it will teach them how to progress from basic predictive models to building advanced models and producing more accurate predictions. Prior knowledge of Python and familiarity with predictive analytics concepts are assumed.
With the following software and hardware list you can run all code files present in the book (Chapter 1-5).
| Chapter | Software required | OS required |
|---|---|---|
| All | Python 3.6 or later | Windows, Mac OS X, and Linux (Any) |
| All | Anaconda 5.2 | Windows, Mac OS X, and Linux (Any) |
| All | Jupyter Notebook | Windows, Mac OS X, and Linux (Any) |
| All | scikit-learn | Windows, Mac OS X, and Linux (Any) |
| All | TensorFlow | Windows, Mac OS X, and Linux (Any) |
We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.
Alan Fontaine Alan Fontaine is a data scientist with more than 12 years of experience in analytical roles. He has been a consultant for many projects in fields such as: business, education, medicine, mass media, among others. He is a big Python fan and has been using it routinely for five years for analyzing data, building models, producing reports, making predictions, and building interactive applications that transform data into intelligence.
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