Descriptions
LEARNING PATH: Statistics for Machine Learning Machine learning is a concern for many developers when it comes to analyzing complex statistical problems. If you know that statistics will help you build powerful machine learning models that optimize a specific problem. In this learning path, you will learn everything you need to perform complex statistical calculations required for machine learning. So, if you are a developer with little or no background in statistics and want to implement machine learning in your systems, then go for this learning path. Packt’s video learning paths are a series of individual video products that are put together in a logical, step-by-step manner so that each video builds on the skills learned in the previous video. You will start with the basics of statistical terminology and machine learning.
You will perform complex statistical calculations required for machine learning and understand the real-world examples that explain the statistical side of machine learning. You will then implement commonly used algorithms for different domain problems by using both Python and R programming. You will use libraries like scikit-learn, NumPy, Random Forest, etc. You will then gain an in-depth knowledge of the different models of unsupervised and reinforcement learning and explore the basics of deep learning using Keras software. Finally, you will get an overview of reinforcement learning using the Python programming language. At the end of this learning path, you will master the necessary statistics for machine learning and be able to apply your new skills to any type of industry problem.
What you will learn
- Introduction to statistical terminology and machine learning
- Provides practical solutions for simple linear regression and multilinear regression
- Implement logistic regression using credit data
- Compares logistic regression and random forest using examples.
- Implement statistical computations programmatically for unsupervised learning through K-Means clustering
- Understand the concepts of artificial neural networks
- Introduce different types of unsupervised learning
Who is this course suitable for?
- This learning path is intended for developers with little or no statistical knowledge who want to implement machine learning in their systems.
Specification of LEARNING PATH: Statistics for Machine Learning
- Publisher : Udemy
- Teacher: Packt Publishing
- Language: English
- Level: Beginner
- Number of courses: 36
- Duration: 4 hours and 11 minutes
Contents of LEARNING PATH: Statistics for Machine Learning
Requirements
- Previous knowledge of Python and R programming is expected.
Pictures
Sample clip
installation Guide
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Subtitles: English
Quality: 720p
Download links
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File size
371MB