Supervised Machine Learning: Regression and Classification

Colleagues, in the “Supervised Machine Learning: Regression and Classification” program you will build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn, and train supervised machine learning models for prediction & binary classification tasks, including linear regression & logistic regression. Develop high-demand skills in Linear Regression, Regularization to Avoid Overfitting, Logistic Regression for Classification, Gradient Descent, and Supervised Learning. The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. In this beginner-friendly program, you will learn the fundamentals of machine learning and how to use these techniques to build real-world AI applications. This 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. Training modules: Week 1: Introduction to Machine Learning - Applications of machine learning, Supervised learning, Supervised learning, Unsupervised learning, Jupyter Notebooks, Linear regression model, Cost function formula and intuition, Visualizing the cost function, Gradient descent, Implementing gradient descent, Learning rate, Gradient descent for linear regression, and Running gradient descent; Week 2: Regression with multiple input variables - learn some methods for improving your model's training and performance, such as vectorization, feature scaling, feature engineering and polynomial regression. At the end of the week, you'll get to practice implementing linear regression in code; and Week 3: Classification - predict categories using the logistic regression model. You'll learn about the problem of overfitting, and how to handle this problem with a method called regularization. You'll get to practice implementing logistic regression with regularization. 

Enroll today (teams & execs welcome): https://imp.i384100.net/555bxN

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)