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Live Webinar: Essentials of Machine Learning

13 Registered Feb, 2019 11:00 AM 2 Hrs

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About the Instructor:

He is an OPTIMISTIK INFOSYSTEMS Accredited Instructor with, more than 10 years of experience in Delivering Training to Corporates in Classroom as well as Online mode. He is a Data scientist, Statistical Modeler Analyst & Big Data trainer in the field of statistical analysis (with management & operational prospective) using technological driven tools & technics including Data Science. AI, BI, Data Analytics, Text mining, NLP, Machine & Deep learning, Cloud computing, IOT, Social media mining, Visual analytics, Big-data set-up like Hadoop, Mahout and Spark.

He is a trainer for Analytic & Statistical modelling on Predictive & Prescriptive Analysis , Time-Series & Demand forecasting, Regression Analysis (Linear to Neural Network to Market Basket analysis), Classification(supervised) & Clustering(unsupervised), Churn, Conjoint & Link Analysis, Market Mix & Market Segmentation, Text mining, Multi-Dimensional scaling, Index creation with tools like Excel, SAS (EG & EM),R,R-Studio, Rev R, SPSS, Python, Rapid Miner, MS azure ML studio, Big-Data, Hadoop, Spark, Mahout, AIML, Cloud Computing. Machine & Deep learning, NLP & Text mining implementer with model deployment using web service. Cloud Computing consultant for SAAS, PAAS, IAAS, NAAS Public, and Private & Hybrid cloud models.

Previously Asst. Professor for Decision Science Area. Visiting faculty for Distributing & cloud computing, Research Methodology, Operational research management, Project management, DW/Data & Advance data mining using SAS, SPSS, Python & ML azure ML studio/Business Intelligence, E-Services in Digital Marketing, Network Economy, Web & Google Analytic, Website analysis, Social media extraction & mining, NLP & Text mining, Building dashboard applications using R, Structural equation modelling using AMOS & LISREL, Face-book & twitter mining, Semantic search(web 3.0). Conducted workshop in corporate along with global certification programs in SAS(Base , Advance, SQL & Macros), SPSS & R, Rapid Miner, Social media impact & leverage,NLP, NLG, Text Mining,Open Text,Cloud Computing, Big-Data, Hadoop, Spark, Data Mining SMAC (Social media, Mobile, Analytic & Cloud computing).

Description

Overview:

What is Machine Learning ?

Machine learning (ML) is a category of algorithm that allows software applications to become more accurate in predicting outcomes without being explicitly programmed. The basic premise of machine learning is to build algorithms that can receive input data and use statistical analysis to predict an output while updating outputs as new data becomes available.


Objectives:

This is an on demand, customized webinar designed for a large set of audience. This is a team at Research Group for a Leading Engineering MNC The core objective is to get an Introduction to Machine Learning so as they can venture into Advanced concepts.


Event Schedule:


Session 1 - Introduction (60 mins):

  1. Machine Learning–Why & How?
  2. Introduction to ML and how it is impacting every business in today’s digitally connected world using qualitative & quantitative data.
  3. Four pillars of ML like -
    1. Understanding of Data & Information.
    2. Why statistics (practical application/tool from mathematics) is considered as foundations of Machine Learning
    3. When to use which analytical model into what programming tools like Excel, R, SAS, Python, SPSS and more
    4. ML’s association with areas like AI, BI, DL, Cloud computing, IOT & IIOT, Big-data Technologies, Block-Chain & Cryptocurrency, Digital/Social media mining in macro economical prospect
  4. Role of Analytics for workforce like Humans & Robots.
  5. When to develop in-house ML solution and at what time a cloud (Azure, AWS, Google) based readymade solution to be deployed.

Conclusion:

  • How to select best ML algorithm/solution for your problem featuring domain/sector.
  • Challenges along with pros & cons (long & short term) for your customized ML solution.

Session 2 - Case Study( 60 mins):

  • Scope- Role of Machine Learning in Healthcare Industry.

Other Events:


Target Audience:

Machine Learning Enthusiast


Delivery Mode:

  • Live Online
  • Instructor Led

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