- 35 (Registered)
When : 11th to 13th June 2020
Course Overview
This course provides a broad introduction to machine learning. It covers statistical inference, regression models, machine learning, and the development of data products.Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). The course will also draw from numerous case studies and application
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Course Content
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Introduction to ML 0/7
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Lecture1.1
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Lecture1.2
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Lecture1.3
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Lecture1.4
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Lecture1.5
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Lecture1.6
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Lecture1.7
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Linear Regression - Case Study & Project 0/8
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Lecture2.1
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Lecture2.2
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Lecture2.3
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Lecture2.4
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Lecture2.5
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Lecture2.6
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Lecture2.7
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Lecture2.8
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Multivarite Linear Regression 0/3
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Lecture3.1
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Lecture3.2
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Lecture3.3
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KNN 0/3
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Lecture4.1
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Lecture4.2
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Lecture4.3
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Decision Trees 0/4
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Lecture5.1
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Lecture5.2
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Lecture5.3
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Lecture5.4
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Bagging and Boosting 0/6
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Lecture6.1
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Lecture6.2
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Lecture6.3
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Lecture6.4
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Lecture6.5
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Lecture6.6
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Support Vector Machine 0/5
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Lecture7.1
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Lecture7.2
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Lecture7.3
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Lecture7.4
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Lecture7.5
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Logistic Regression 0/7
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Lecture8.1
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Lecture8.2
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Lecture8.3
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Lecture8.4
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Lecture8.5
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Lecture8.6
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Lecture8.7
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Clustering 0/5
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Lecture9.1
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Lecture9.2
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Lecture9.3
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Lecture9.4
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Lecture9.5
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Recommendation Systems 0/2
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Lecture10.1
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Lecture10.2
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Instructor
Arun Panayappan is the Founder of Techcovery Solutions which has been in the training and consulting business for three years now. Arun Panayappan was the Vice President, Platform Engineering at www.goibibo.com which is India’s largest online travel agent. He has over 23 years of IT experience including 4 years of overseas experience.Techcovery has trained over 1000 participants in Data science and mentored 4 start ups during its existence. He has worked as a consulting CTO for companies like cogknit semantics, FirstIPO and Trip38. He is frequently consulted for data science architecture and strategy by corporations across the industry. In his role at Amazon, his technical decision-making skills enabled Kindle Topaz Operations Console to go global and scale seamlessly to meet seasonal load. He drove initiatives to hire and develop the best for the Category Expansions team that doubled in size during his leadership tenure while launching 70 new stores for www.amazon.com every year. He built highly scalable web crawling systems to monitor price changes at competitor sites for millions of products sold by Amazon. This system used statistical machine learning and modeled crawl frequencies using poison distribution. His team built the on-boarding experience of vendor platform(https://vendorexpress.amazon.com) to onboard and manage small and medium size vendors to increase selection and buying options. Prior to joining Amazon, he worked for Kuliza (www.kuliza.com), young start up by ex-Amazon employees, and had served the Research team at Accenture Technology Labs., India. He is an innovative and a tech-savvy leader. He sets a high bar for himself and his team on software design, quality and processes. He has a pleasing personality and excellent communication skills.