Have you ever wondered how to apply machine learning to business problems? This workshop is specially designed to help learn the concepts, tools and techniques involved. You will go through real-life case studies and experience how this is done in the industry. The focus of this workshop will be on the machine learning pipeline data cleaning, feature engineering, model building and evaluation. You will also learn how to structure a business problem as an ML problem, and then go on to build, select and evaluate the model.
Check out the structure of the workshop here : Applied Machine Learning
Amit Kapoor teaches the craft of telling visual stories with data. He conducts workshops and trainings on Data Science in Python and R, as well as on Data Visualisation topics.His background is in strategy consulting having worked with AT Kearney in India, then with Booz & Company in Europe and more recently for startups in Bangalore. He did his B.Tech in Mechanical Engineering from IIT, Delhi and PGDM (MBA) from IIM, Ahmedabad.
Interacting with artificial intelligent systems seems a bit simulated at times. This is because the way we converse as humans to one another is completely different from that we do usually with AI systems.Thankfully, research has been rampant in the area to bridge the gap in conversational AI systems. In this 8-hour workshop, you will get to know about natural language processing, creating word embeddings and developing learners to perform NLP tasks like sentiment analysis, auto correction and much more.
Here is the detailed structure of the workshop : Getting started with Natural Language Processing
Dipanjan (DJ) Sarkar is a Data Scientist, a published author and a consultant and trainer. He has consulted and worked with several startups as well as Fortune 500 companies like Intel. He primarily works on leveraging data science, advanced analytics, machine learning and deep learning to build large- scale intelligent systems. He holds a master of technology degree with specializations in Data Science and Software Engineering. He is also an avid supporter of self-learning and massive open online courses. He plans to venture soon into the world of open-source products to improve the productivity of developers across the world.
Dipanjan has been an analytics practitioner for several years now, specializing in machine learning, natural language processing, statistical methods and deep learning. Having a passion for data science and education, he also acts as an AI Consultant and Mentor at various organizations like Springboard, where he helps people build their skills on areas like Data Science and Machine Learning. He also acts as a key contributor and editor for Towards Data Science, a leading online journal focusing on Artificial Intelligence and Data Science. Dipanjan has also authored several books on R, Python, Machine Learning, Social Media Analytics, Natural Language Processing Deep Learning.
Raghav Bali is a Data Scientist at one the world’s largest healthcare organizations. His work involves research development of enterprise level solutions based on Machine Learning, Deep Learning and Natural Language Processing for Healthcare Insurance related use cases. In his previous role at Intel, he was involved in enabling proactive data driven initiatives using Natural Language Processing, Deep Learning and traditional statistical methods. He has also worked in the financial domain with American Express, solving digital engagement and customer retention use cases. Raghav has also authored multiple books with leading publishers, the recent one on latest in advancements in Transfer Learning research. Raghav has a master’s degree (gold medalist) in Information Technology from International Institute of Information Technology, Bangalore. Raghav loves reading and is a shutterbug capturing moments when he isn’t busy solving problems.