Taksha Academy e-Seminar Series (TeSS): Introduction to AI/Machine Learning

Date April 15, 2020 and 4 following Wednesdays
4:00 – 5:30 PM ET (1:00 to 2:00 PM PT)
Director Professor Rao Vemuri, PhD, Chair of the Taksha Center for Machine Learning and Hydrology (TCMLH – www.taksha.org/divisions/TCMLH), and Distinguished Member of the Technical Advisory Committee (TAC) for the Taksha Center of Data Science (TCDS – www.taksha.org/divisions/TCDS); Emeritus Professor, University of California, Davis (See bio at www.taksha.org/advisors/vemuri.)


This e-Seminar series is designed to introduce to the novice the current trends and market needs of Machine Learning (ML), which is changing the world. To use ML effectively, one needs to understand the algorithms involved and how to put them to use. This series of online sessions provides an introduction into the most popular machine learning algorithms, using the popular SciKit-Learn package in Python language. The seminars teach ML from a practical perspective; in-depth coverage of Math / Stats is beyond the scope of this course.

The free series begins on Wednesday, April 15 for five consecutive Wednesdays from 4:00pm – 5:30pm.

Access details will be provided to registrants closer to the start date.

Intended Audience:
 Fresh graduates who are anxious to launch a career in Machine Learning
 Working professionals who wish to make a switch to this exciting area
 Professionals who wish to keep up to date with the latest trends
 Data analysts, Software Engineers, Data scientists

Course Outline:
1. Why Machine Learning is important
2. What is Machine Learning?
3. Importance of data in Machine Learning. Where to get data?
4. Posing the standard Machine Learning problem in math notation.
5. Classification Vs regression. Linear regression. Gradient descent method.
6. Logistic regression and the binary classification problem. Probabilistic interpretation
7. Running Examples: (i) Estimating the price of a house. (ii) Classification of tumors as
benign or malignant
8. Coding in Python & Scikit-Learn using Jupyter notebook.

(a) At a minimum, you should have high school level calculus. Ideally, you should know
logarithms, exponentials, the chain rule of differentiation, vector-matrix notation,
and dot product of two vectors.
(b) You should be comfortable using computers. Familiarity with Python programming is a plus.

What is Expected from You:
 Attend all five sessions and spend at least one hour at home for each one hour spent in class
 Have a reasonably modern laptop with unrestricted connection to the Internet.
 A browser (Chrome)
 Install the Anaconda distribution of Python (it comes with Jupyter Notebook, Numpy, Pandas and Scikit-Learn)
 If you are not familiar with the above bullet, ask a Python Guru


This seminar series is being offered on a complementary basis, although we require advance registration. A Certificate of Completion will be given to those who attend all five sessions.

Please register for the series below.


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DISCLAIMER: Attendance at this event is for personal growth, and entails no promise of employment.