Data Science with Python: Combine Python with machine learning principles to discover hidden patterns in raw data

Rohan Chopra

England

Mohamed Noordeen Alaudeen

€29.99

3 (1 Ratings)

Paperback Jul 2019 426 pages 1st Edition

Rohan Chopra

England

Mohamed Noordeen Alaudeen

€29.99

3 (1 Ratings)

Paperback Jul 2019 426 pages 1st Edition

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Key benefits

Gain useful insights into data science, from data collection through to visualization
Get up to speed with pandas, scikit-learn, and Matplotlib
Study a variety of data science algorithms using real-world datasets

Description

Data Science with Python begins by introducing you to data science and teaches you to install the packages you need to create a data science coding environment. You will learn three major techniques in machine learning: unsupervised learning, supervised learning, and reinforcement learning. You will also explore basic classification and regression techniques, such as support vector machines, decision trees, and logistic regression. As you make your way through the book, you will understand the basic functions, data structures, and syntax of the Python language that are used to handle large datasets with ease. You will learn about NumPy and pandas libraries for matrix calculations and data manipulation, discover how to use Matplotlib to create highly customizable visualizations, and apply the boosting algorithm XGBoost to make predictions. In the concluding chapters, you will explore convolutional neural networks (CNNs), deep learning algorithms used to predict what is in an image. You will also understand how to feed human sentences to a neural network, make the model process contextual information, and create human language processing systems to predict the outcome. By the end of this book, you will be able to understand and implement any new data science algorithm and have the confidence to experiment with tools or libraries other than those covered in the book.

Who is this book for?

Data Science with Python is designed for data analysts, data scientists, database engineers, and business analysts who want to move towards using Python and machine learning techniques to analyze data and predict outcomes. Basic knowledge of Python and data analytics will prove beneficial to understand the various concepts explained through this book.

What you will learn

Pre-process data to make it ready to use for machine learning
Create data visualizations with Matplotlib
Use scikit-learn to perform dimension reduction using principal component analysis (PCA)
Solve classification and regression problems
Get predictions using the XGBoost library
Process images and create machine learning models to decode them
Process human language for prediction and classification
Use TensorBoard to monitor training metrics in real time
Find the best hyperparameters for your model with AutoML

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C.T. Wong Apr 11, 2021

For a novice at data science, I found most of what I needed to get started in this book but if you are not a fan of constantly having to refer to another section in the middle of the chapter there are probably other books with better layouts. Personally I prefer all my information in one place and flowing smoothly - having to read about PCA and then flip forwards and backwards because the author has recycled information from elsewhere instead of printing it out twice got annoying. I bought the hard copy so can at least keep the pages open with paper weights - I'm not sure how well this works with the ebook.

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Data Science with Python: Combine Python with machine learning principles to discover hidden patterns in raw data

What do you get with Print?