Online Workshop on Regression and Classification using Python


Regression and Classification using Python Workshop was a series of webinar session held on 22nd -24th May, 2020. Event was organized by Department of Information Technology G H Patel College of Engineering & Technology in collaboration with Computer Society of IEEE GCET Student Branch. The main aim of the webinar series was to puzzle out basic knowledge of Machine Learning, topics like Data Preprocessing Introduction, Data Preprocessing Hands-on, and Introduction to Regression, Regression Algorithm Hands-On, Classification Algorithm and Classification Hands-on using Python.

Day 1: The first session was conveyed by Prof. Yogesh Dangar based on introduction to Machine Learning and made us understand which tools and technology used to write python script, next topic was Introduction to Regression models such as Linear and Non Linear used to predict real values and explain us the hands on programs on Regression. Around 65 students actively attend the webinar. Further he explained Supervised and unsupervised learning are the machine learning paradigms which are used in solving the class of tasks by learning from the experience and performance measure.These supervised and unsupervised learning techniques are implemented in various applications such as artificial neural networks which data processing systems are containing a huge number of largely interlinked processing elements. Finally he ended sessions after explaining hands-on program of Data Preprocessing Python code for our reference and giving students quiz to solve.

Day 2: Second day of workshop on Regression and Classification using Python was also conducted by Prof. Yogesh Dangar, he continue the session by explaining one more hands-on program , he explain how to create a simple linear regression model using numpy,matplotlib,pandas libraries.Around 65 students actively attend the webinar. The program target a prediction value based on independent variables. It is mostly used for finding out the relationship between variables and forecasting, explain code snippet of separate matrix feature and DV,Splitting dataset in testing and training,predict the result on test data,plotting the results on graph.

Day 3: The third session of Regression and Classification using Python was conducted by Prof. Vinita Shah. Topics covered my Ma’am was Classification, Difference between Classification and Regression, Flow Steps of Implementation, Feature Scaling and Classification Algorithm Implementation. Moving ahead she insight Problems which have a categorical answer, as in problems which have a fixed solution is defined as a Classification by giving example on Classification problems and engaging students with her witty questions, also gave an difference between Regression and Classification by using simple terminologies, she acquired students by teaching different types of algorithm used in the Classification Problems and explained each terminologies by giving program related to example. Finally, she concluded the session by explaining hands-on problems like naïve-bayes, numpy-reshape, and numpy-concatenate programs and answering the queries of different students.

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Department: Information Technology