- 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
- 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
- You'll need a desktop computer
- Some prior coding or scripting experience is required.
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.
- 10 Reviews
- 150 Students
- 19 Courses
We make the students' society proud as they work with real-time applications on which they can happily lead their life. The students who work for their dreams can use this experience to fulfill their dreams. We believe that only smart work makes the world of robotics nation proud and great.
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