Sale Date Ended
Rs.19500 (300 US Dolloars)
Date: Nov 21st to Nov 29th 2015
Timings: 8:30 pm - 10:00 pm, Indian Standard Time +5:30 GMT
Mode of Training: Online Instructor Led
Hurry up, and book your slot right away as the tickets are selling fast. Learn, explore and enrich your knowledge in Big Data technologies. Come, unleash the power of Practical Machine Learning by experts Dr.Srinivas Padmanabhnuni and Neelima Vobugari from the industry.
Certificate : Yes
Practical Machine Learning from Dr.Srinivas Padmanabhuni & Neelima Vobugari
Tarah Technologies is glad to give you the opportunity to learn concepts of Machine Learning and Big Data from Dr.Srinivas and Neelima Vobugari from a practical angle. He is a veteran in IT industry having filed and raised multiple patents. Dr.Srinivas has a Ph.D in Artificial Intelligence from University of Alberta, Canada. He secured his B.Tech and M.Tech from IIT Kanpur and IIT Mumbai respectively.
Dr.Srinivas was spearheading research in Infosys till October 2015. He is the President of ACM India and has delivered invited lectures in universities and conferences across the world, some of them being Purdue (USA), CMU (USA), USC (USA), UoW (Australia), Mindef (Singapore), IIT(s) (India), IIIT(s)(India), NIT(s) (India) etc.
Dr.Srinivas has consulted on practical problems across verticals ranging from financial services, retail, utilities to transportation leveraging his expertise in Analytics, Data Science, Machine Learning, Software Engineering and Enterprise Architecture
LinkedIn Profile: https://www.linkedin.com/in/spadmanabhuni
Neelima Vobugari is founder of Tarah Technologies, http://www.tarahtech.com. She is a certified CRM consultant and a certified Data Scientist. She is an alumnus of John Hopkins University, Maryland, where she finished her specialization in Data Sciences. She has worked on interesting real-time data science and customer centric CRM projects. Before starting Tarah Technologies, she worked for giant IT companies including IBM. She was invited by the Chief Minister of Karnataka for the pre-budget session of Karnataka for representing the women entrepreneurs of Karnataka where she suggested the measures to be taken to encourage more women entrepreneurs. She has also attended the International Women Entrepreneur Conference held at Minneapolis, USA in 2013 and represented India.
Practical Machine Learning
Machine Learning helps you in the extraction of patterns present in the data which are non-trivial. Big Data is everywhere, be it webspace, social media, supermarket transactions, bank transactions etc. Big Data is data which is so huge that it is unable to process through traditional statistical methods. The webinar titled “Practical Machine Learning" gives the participant a bird’s eye view of Big Data technologies. The participants will appreciate the applications of Machine Learning starting from predicting weather, diagnosing malignant diseases based on the history of patient’s records to recently developed Google’s self driving car.
The online webinar will enable the attendees to use different machine learning algorithms based on the available data in a practical scenario. These demonstrations will be done via User Interface (UI) tools and sample production data. The participants need not have expert programming skills, but basic computer skills are advised.
The target audience includes:
Topics Covered in the workshop
The workshop will emphasize on the following topics:
a. Relevance of Big Data
b. Relevance of Machine Learning
c. Artificial Intelligence and Machine Learning
d. Use Cases across verticals
e. Overview of Supervised and Unsupervised Machine Learning Techniques
2. Regression Models
a. Linear Regression
b. Logistic Regression
3. Supervised Learning Models
a. Support Vector Machine
b. Decision Trees
c. Boosting, Bagging and Stacking
d. Random Forest
4. Unsupervised Learning Models
a. K-means clustering
b. Alternative Clustering Models
5. Association Rule Mining Algorithms
a. Apriori Algorithm
6. Text Mining Use Cases and Algorithms
a. Named Entity Resolution
b. Social Media Analytics
7. Advanced Topics
a. Deep Learning
b. Social Network Analysis
This course will enable you to: