Machine Learning with Python: from Linear Models to Deep Learning (MITx)

Colleagues, the “Machine Learning with Python: from Linear Models to Deep Learning” program offers an in-depth introduction to the field of machine learning, from linear models to deep learning and reinforcement learning, through hands-on Python projects. In this course, you will learn about principles and algorithms for turning training data into effective automated predictions, representation, over-fitting, regularization, generalization, VC dimension, clustering, classification, recommender problems, probabilistic modeling, reinforcement learning, and on-line algorithms, support vector machines, and neural networks/deep learning. Students will implement and experiment with the algorithms in several Python projects designed for different practical applications. Skill-based training modules include: 1) Understand principles behind machine learning problems such as classification, regression, clustering, and reinforcement learning, 2) Implement and analyze models such as linear models, kernel machines, neural networks, and graphical models, 3) Choose suitable models for different applications, and 4) Implement and organize machine learning projects, from training, validation, parameter tuning, to feature engineering.

Enroll today (teams and execs are welcome): https://edx.sjv.io/oNP9ao 

Recommended Reading:

1 - “AI Software Engineer: ChatGPT, Bard & Beyond” (Audible) or (Kindle)  

2 - “ChatGPT, Gemini and Llama - The Journey from AI to AGI, ASI and Singularity” (Audible) (Kindle)

3 - “The Upskill Gambit - Discover the 5 Keys to Your Career and Income Security in the Digital Age” (Audible) (Kindle)

Much success in your AI career, AI Academy (please subscribe and share with you colleagues)