Essential Math, Python and Tensorflow for Machine Learning
Time & Location
About the Event
Instructors: Dr. Kiran Gunnam, Dr. Koji Seto, Dr. Osso Vahabzadeh
What you will learn / Topics that will be covered:
1. Introduction to Machine Learning: What is Machine Learning? Applications, History of machine learning, Traditional machine learning, Machine learning techniques - Supervised, Unsupervised, Reinforcement, Imitation
2. Math Basics: Linear algebra, Probability, Least squares approximation, Gradient Descent
3. Python Basics: Mathematical computing, Statistical analysis, Data visualization
4. Tensorflow Basics: Computational graph, Tensorflow APIs, Visualization, Debugging, Examples (XOR), Comparison with PyTorch
Engineers, researchers, practitioners and students who are interested in machine learning, convolutional neural networks, recurrent neural networks, reinforcement learning and their implementations on GPUs. This workshop will particularly benefit people who intend to learn machine learning techniques and are unsure of your level of technical skills/background knowledge.
Basic knowledge of matrices, vectors, derivatives, probability, and familiarity with basic programming fundamentals.
Upon completion of this course, you’ll be ready to learn about Machine Learning and Deep Learning by using basic knowledge of math and technical skills in Python and Tensorflow that you obtained through the course.