Please wait...

Supervised Learning with Python

Supervised Learning with Python


  • Author: Vaibhav Verdhan
  • ISBN: 1484261550
  • Year: 2020
  • Pages: 392
  • Language: English
  • File size: 9.3 MB
  • File format: PDF, ePub
  • Category: Python

Book Description:

Gain a thorough understanding of supervised learning algorithms by developing use cases with Python. You will study supervised learning concepts, Python code, datasets, best practices, resolution of common issues and pitfalls, and practical knowledge of implementing algorithms for structured as well as text and images datasets.

You’ll start with an introduction to machine learning, highlighting the differences between supervised, semi-supervised and unsupervised learning. In the following chapters you’ll study regression and classification problems, mathematics behind them, algorithms like Linear Regression, Logistic Regression, Decision Tree, KNN, Naïve Bayes, and advanced algorithms like Random Forest, SVM, Gradient Boosting and Neural Networks. Python implementation is provided for all the algorithms. You’ll conclude with an end-to-end model development process including deployment and maintenance of the model.After reading Supervised Learning with Python you’ll have a broad understanding of supervised learning and its practical implementation, and be able to run the code and extend it in an innovative manner.

What You’ll Learn

  • Review the fundamental building blocks and concepts of supervised learning using Python
  • Develop supervised learning solutions for structured data as well as text and images
  • Solve issues around overfitting, feature engineering, data cleansing, and cross-validation for building best fit models
  • Understand the end-to-end model cycle from business problem definition to model deployment and model maintenance
  • Avoid the common pitfalls and adhere to best practices while creating a supervised learning model using Python
Who This Book Is For
Data scientists or data analysts interested in best practices and standards for supervised learning, and using classification algorithms and regression techniques to develop predictive models.

Download

Supervised Learning with Python.pdf

Automatically open website of the sponsor when clicking download

Related eBooks
Advanced Analytics in Power BI with R and Python
ISBN: 1484258282
Author: Ryan Wade
Category: Python
Machine Learning Concepts with Python and the Jupyter Notebook Environment
ISBN: 1484259661
Author: Nikita Silaparasetty
Category: Python
Advanced Python Development
ISBN: 1484257928
Author: Matthew Wilkes
Category: Python
Python Workout
ISBN: 1617295507
Author: Reuven M. Lerner
Category: Python
Deep Learning with Pytorch
ISBN: 1617295264
Author: Eli Stevens
Category: Python
Beginning Sensor Networks with XBee, Raspberry Pi, and Arduino, Second Edition
ISBN: 1484257952
Author: Charles Bell
Category: Python
Django Standalone Apps
ISBN: 148425631X
Author: Ben Lopatin
Category: Python
Thinking in Pandas
ISBN: 148425838X
Author: Hannah Stepanek
Category: Python