Hands-On Predictive Analytics with Python

This is the code repository for Hands-On Predictive Analytics with Python, published by Packt.

Master the complete predictive analytics process, from problem definition to model deployment

What is this book about?

This book will teach you all the processes you need to build a predictive analytics solution: understanding the problem, preparing datasets, exploring relationships, model building, tuning, evaluation, and deployment. You'll earn to use Python and its data analytics ecosystem to implement the main techniques used in real-world projects.

This book covers the following exciting features:

• Get to grips with the main concepts and principles of predictive analytics
• Learn about the stages involved in producing complete predictive analytics solutions
• Understand how to define a problem, propose a solution, and prepare a dataset
• Use visualizations to explore relationships and gain insights into the dataset
• Learn to build regression and classification models using scikit-learn
• Use Keras to build powerful neural network models that produce accurate predictions
• Learn to serve a model's predictions as a web application

If you feel this book is for you, get your copy today!

Instructions and Navigations

All of the code is organized into folders. For example, Chapter02.

The code will look like the following:

carat_values = np.arange(0.5, 5.5, 0.5)
preds = first_ml_model(carat_values)
pd.DataFrame({"Carat": carat_values, "Predicted price":preds})

Following is what you need for this book: This book is aimed at data scientists, data engineers, software engineers, and business analysts. Also, students and professionals who are constantly working with data in quantitative fields such as finance, economics, and business, among others, who would like to build models to make predictions will find this book useful. In general, this book is aimed at all professionals who would like to focus on the practical implementation of predictive analytics with Python.

With the following software and hardware list you can run all code files present in the book (Chapter 1-13).

Software and Hardware List

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.

Related products

• TensorFlow: Powerful Predictive Analytics with TensorFlow [Packt] [Amazon]

• Building Machine Learning Systems with Python - Third Edition [Packt] [Amazon]

Get to Know the Author

Alvaro Fuentes is a data scientist with more than 12 years of experience in analytical roles. He holds an M.S. in applied mathematics and an M.S. in quantitative economics. He worked for many years in the Central Bank of Guatemala as an economic analyst, building models for economic and financial data. He founded Quant Company to provide consulting and training services in data science topics and has been a consultant for many projects in fields such as business, education, medicine, and mass media, among others.

He is a big Python fan and has been using it routinely for five years to analyze data, build models, produce reports, make predictions, and build interactive applications that transform data into intelligence.

Suggestions and Feedback

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