According to Indeed study, machine learning engineering is the best job in the United States, analyzing the average salaries $146,085 (an astounding 344% increase since 2015) and job posting growth between 2015 and 2018.
ML is a ocean, there are so many courses, resources by which one can get easily confused so in this post I will share top free machine learning courses you can take and get started with both conceptual and practical knowledge.
Top 4 Best Free ML course
Let’s get in to details about courses and topics covered.
#1. Machine Learning – Coursera by Andrew Ng
This course provides a broad introduction to ML, datamining, and statistical pattern recognition.
Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI).
#2. Machine Learning Crash Course by Google developer
ML Crash Course features a series of lessons with video lectures, real-world case studies, and hands-on practice exercises.
Learn and apply fundamental ML concepts with the Crash Course, get real-world experience with the companion Kaggle competition, or visit Learn with Google AI to explore the full library of training resources.
#3. Learn-ML by tensorflow
To become an expert, you first need a strong foundation in four learning areas: coding, math, ML theory, and how to build your own ML project from start to finish.
Begin with TensorFlow’s curated curriculums to improve these four skills, or choose your own learning path by exploring our resource library below.
AI For Everyone is taught by Dr. Andrew Ng, a global leader in AI and co-founder of Coursera. Dr. Ng is also the CEO and founder of deeplearning.ai and founder of Landing AI. He is an Adjunct Professor in the Computer Science Department at Stanford University.
It is a non-technical 4 week course, will help you understand AI technologies and spot opportunities to apply AI to problems in your own organization.
You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started.
You can find buy link below, also if you search book name you will find ebook of this book.
Seedbank, a place to discover interactive ML examples which you can run from your browser, no set-up required. Each example is a little seed to inspire you that you can edit, extend, and grow into your own projects and ideas, from data analysis problems to art projects.
Some of best channels on YouTube that will help in getting machine learning concepts more clear are mentioned below.
- Microsoft Research
- Google Developers
- Code Emporium
- Josh Gordon
- NPTEL-NOC IITM
Hope you like this article on Machine Learning courses, join these courses, complete it and start doing projects, program as many code on google colab or jupyter notebook and sky rocket your career in ML.