Training Your Systems with Python Statistical Modeling Free Download
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Training Your Systems with Python Statistical Modeling, FreeTuts Download

Training Your Systems with Python Statistical Modeling, FreeTuts Download

Training Your Systems with Python Statistical Modeling – Learning statistical systems with Python

Python, a multi-paradigm programming language, has become the language of choice for data scientists for data analysis, visualization, and machine learning. This course takes you through the various different concepts that get you acquainted and working with the different aspects of Machine Learning.

You’ll start by diving into classical statistical analysis, where you will learn to compute descriptive statistics with Pandas. From there, you will be introduced to supervised learning, where you will explore the principles of machine learning and train different machine learning models. Next, you’ll work with binary prediction models, such as data classification using K-nearest neighbors, decision trees, and random forests.

After that, you’ll work with algorithms for regression analysis, and employ different types of regression, such as ridge and lasso regression, and spline interpolation using SciPy. Then, you’ll work on neural networks, train them, and employ regression on neural networks. You’ll be introduced to clustering, and learn to evaluate cluster model results, as well as employ different clustering types such as hierarchical and spectral clustering. Finally, you’ll learn about the dimensionality reduction concepts such as principal component analysis and low dimension representation.

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Training Your Systems with Python Statistical Modeling, FreeTuts Download

Info Tutorials/Courses

Manufacturer: Pocket Publishing / Packt Publishing
Language: English Curriculum 
Curtis Miller
Education Level: Advanced
Training Time: 4 hours +
File Size: 961 MB

Download Tutorials/Courses

Download Link Google Drive Download Link Google Drive 2

 Download Link OneDrive Download on Box.com

Password : freetuts.download

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About the Author: Ho Quang Dai

I am Ho Quang Dai. Looking forward to receiving positive contributions from readers

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