Machine Learning Specialization

Colleagues, the Machine Learning Specialization taught by Andrew Ng is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. BreakIntoAI with Machine Learning Specialization. Master fundamental AI concepts and develop practical machine learning skills in the beginner-friendly, 3-course program. Gain high demand skills in Logistic Regression, Artificial Neural Network, Linear Regression, Decision Trees and Recommender Systems. This beginner-friendly program will teach you the fundamentals of machine learning and how to use these techniques to build real-world AI applications.\n\nThis Specialization is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field. This 3-course Specialization is an updated version of Andrew’s pioneering Machine Learning course, rated 4.9 out of 5 and taken by over 4.8 million learners since it launched in 2012. This 3-course Specialization is an updated version of Andrew’s pioneering Machine Learning course, rated 4.9 out of 5 and taken by over 4.8 million learners since it launched in 2012. Build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn.Build and train supervised machine learning models for prediction and binary classification tasks, including linear regression and logistic regression. Build and train a neural network with TensorFlow to perform multi-class classification. Apply best practices for machine learning development so that your models generalize to data and tasks in the real world. Build and use decision trees and tree ensemble methods, including random forests and boosted trees. Use unsupervised learning techniques for unsupervised learning: including clustering and anomaly detection. Build recommender systems with a collaborative filtering approach and a content-based deep learning method. Build a deep reinforcement learning model. Skill-based lessons include: 1) Supervised Machine Learning: Regression and Classification, 2) Advanced Learning Algorithms and 3) Unsupervised Learning, Recommenders, Reinforcement Learning.

Enroll today (teams & execs welcome): https://tinyurl.com/yc5c8snp 

Download your free AI-ML-DL - Career Transformation Guide.

For your listening-reading pleasure:

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

2 - “ChatGPT - The Era of Generative Conversational AI Has Begun” (Audible) or (Kindle) 

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

Much career success, Lawrence E. Wilson - AI Academy (share with your team)