Machine Learning using Python

Complete hands-on machine learning and AI tutorial with Python, TensorFlow, Deep Learning, Recommendation Engines, and Neural networks

Intermediate 0(0 Ratings) 0 Students enrolled
Created by Allashyam Charan Last updated Fri, 09-Feb-2024 English
What will i learn?
  • Make predictions using linear regression, polynomial regression, and multivariate regression
  • Implement machine learning at massive scale with Apache Spark's MLLib
  • Build artificial neural networks with Tensorflow and Keras
  • Build a movie recommender system using item-based and user-based collaborative filtering

Curriculum for this course
8 Lessons 10:36:58 Hours
Machine Learning using Python
8 Lessons 10:36:58 Hours
  • 1 Getting Started with Stats 01:14:09
  • 2 ML using Python 01:47:59
  • 3 Recommendation Engines 00:38:51
  • 4 Data Mining and Big Data 02:52:41
  • 5 Experimental Design 00:55:15
  • 6 Deep Learning 02:51:16
  • 7 Final Project 00:06:20
  • 8 Review 00:10:27
Requirements
  • You'll need a desktop computer
  • Some prior coding or scripting experience is required.
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Description

Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Uber extract meaning and insights from massive data sets, this data science course will give you the fundamentals you need. Data Scientists enjoy one of the top-paying jobs, with an average salary of $120,000 according to Glassdoor and Indeed. That's just the average! And it's not just about money - it's interesting work too!

If you've got some programming or scripting experience, this course will teach you the techniques used by real data scientists and machine learning practitioners in the tech industry - and prepare you for a move into this hot career path. This comprehensive machine learning tutorial includes 10+ hours of video, and most topics include hands-on Python code examples you can use for reference and for practice.

Each concept is introduced in plain English, avoiding confusing mathematical notation and jargon. It’s then demonstrated using Python code you can experiment with and build upon, along with notes you can keep for future reference. You won't find academic, deeply mathematical coverage of these algorithms in this course - the focus is on practical understanding and application of them. 

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About the instructor
  • 10 Reviews
  • 150 Students
  • 19 Courses
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Includes:
  • 10:36:58 Hours On demand videos
  • 8 Lessons
  • Access on mobile and tv
  • Full lifetime access
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