Summer School '21
IEEE Student Branch DAIICT aims to provide an interactive and informative platform for students to develop professional and technical abilities. IEEE SB DAIICT hosts Summer School every year to provide students an opportunity to develop their technical skills and make their summer break a productive one.
This time we bring to you a 5 day-long, Summer School 2021. This summer school aims at providing a hands-on experience in one of the emerging technical domains followed by a competition and exciting prizes to grab.
The domain for Summer School 2021 is
Data Science and Machine Learning.
The event will take place on:
4th, 5th and 6th June 2021 - Data Science and Machine Learning Hands-on
12th and 13th June 2021- Advanced Machine Learning Algorithms and Industrial Project
Principal Data Scientist | Author | Speaker | Thought Leader | Co-founder at Profond AI
Mr. Akshay is a renowned Artificial Intelligence and Machine learning evangelist and a thought leader. He is awarded Top 40 Data scientists under 40 in India by Analytics India Magazine. He has rich experience in building and scaling AI and Machine Learning businesses and creating significant client impact. Previously, he was part of Gartner and Accenture, where he scaled the analytics and data science business. He has published international books on Data Science/ Artificial Intelligence with Packt and Apress and currently authoring a book on Next-Gen AI with Oreilly.
Data Scientist | Author | Speaker | AI educator | Co-founder at Profond AI
Mr. Adarsha is an Analytics and Data Science Expert and he is leading a group of data scientists who enable marketing strategies through ML and AI. He is also actively involved in R&D on NLP for creating next-gen AI products. His rich experience and expertise involve business understanding, Statistics, Machine Learning, and Deep Learning. Previously, he was part of Tredence Analytics and IQVIA, where he was involved in delivering high-quality Analytics and Data science products in the e-commerce domain. Recently, he published a book on NLP with Apress and authoring another with Packt.
What is Statistics?
Computing basic statistics
Hypothesis Testing
Statistical tests - Correlation, Chi Square, ANOVA
Summarizing Data
Data Analysis Pipeline
Processing the Data
Types of Data
Feature engineering
Data Wrangling
Exploratory Data Analysis
Visualization of Data
Life cycle of Data Science
What is Machine Learning?
Machine Learning Use-Cases
Machine Learning Process Flow
Machine Learning Categories
Supervised Learning: Linear Regression, Logistic Regression
What is Classification and its use cases?
What is a Decision Tree?
Algorithm for Decision Tree
Confusion Matrix
Random Forest algorithm in detail
Support Vector Machine: Classification
Implementing all the algorithms in Python in the form of an industry level project.
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