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Overview of the event

Machine Learning Day will be happening on 2nd February, 2019 in Pune.

Machine learning is a field of artificial intelligence that uses statistical techniques to give computer systems the ability to "learn from data, without being explicitly programmed.

The Event “Machine Learning Day” is a Program being curated based on guidelines from industry experts. The theme of this conference is to emphasise on the industry best practices needed for Machine Learning to learn the latest in the Machine Learning domain.



Facts & Figures About The Event

7 Speakers
7 Topics
50 Tickets

Our Past Speakers


Srivatsan Santhanam

Sr Director

S4HANA


Awantik Das

Co-Founder | AI Speaker | Corporate Trainer

EdYoda, Zeke Labs


Muralidhar Sridhar

Vice President, Centre of Excellence AI and Machine Learning and Advisor

Prime Focus Technologies


Sachin Mudholkar

VP Technology

Relatas - Sales AI


Bharath Hemachandran

Principal Consultant

Thoughtworks


Siddheshwar Jain

Technology and Transformation Specialist

Formerly Oracle, SocGen and Fidelity


Usha Rengaraju

Sr Data Scientist, Polymath & Ambassador

neoEYED inc, AIMed


Chandra Bhanu Jha

Data Scientist, Author & Founder

American Express

Conference Schedule

Machine Learning Day (2nd February, 2019)
X Topic Abstract

Customer Lifetime Value has been the mirage which most of the large customer centric organizations globally are chasing for decades. Calculating the value in any meaningful way is the first thing but then making those calculations in real time and giving the lifetime value true legs by making it actionable... well that's a mirage worth chasing.
Hear Yogendra Joshi, Director Product Management for Loyalty solutions at Oracle share his journey into the customer experience and why he thinks that the Machine Learning can hold the key towards solving this difficult puzzle and also raise some interesting ideas for all of you to participate in.

Speaker Profile

Executive with experience in software product strategy, product management, development and delivery of enterprise scale products. Currently Head of Product Management and Strategy for Loyalty / CX Solutions at Oracle. Globally recognized Customer Experience expert helping largest and best Loyalty programs become successful by building world leading Loyalty Solutions. Chartered Accountant (CPA Equivalent) with strong expertise in Management and Execution of Product Lifecycle for both ERP (Financials) and CRM products.
Three software Patents filed in the area of Customer Loyalty Management, Customer Experience and Partner Billing.
Experience in "concept - to - market leadership" for software products:
- Generating new product idea,
- Creating business plans and investment proposals,
- Building teams to build enterprise class, innovative software solutions,
- Taking the products successfully to market,
- Help customers and partners achieve greater value from the products,
- Achieve and maintain market leadership.

X Topic Abstract

Explore the ways in which ML models can be used for Natural language processing. Evolution in the models over the recent past. Explain concept of Convolutional neural network, its variants like RNN and others. . Explain how CNN and RNN are use for chatbots, sentiment analysis, machine translation. Present a short demo on any one application of ML in NLP


X Topic Abstract

There are bunch of Machine learning methods and they have a variety of applications in different industries. We will understand it in detail covering these points.
What are different Machine Learning methods and their types? A process applied in machine learning methods - Data acquisition, pre-processing, feature extraction and processing, model learning, evaluation, deployment. Know how to decide which machine learning algorithm need to be used when. Understand the data before finalizing the algorithm. A broad classification of machine learning application - Text Analytics, Quantitative Analysis, and Computer Vision. Machine learning application in day to day life. Future applications of machine learning.

Speaker Profile

Karimkhan is a Data Scientist at BigData Analytics Organization - Datametica. He has more than 5 years of experience in applying Data science in various use cases for Social media, Stock Market, Healthcare, E-Commerce, Lifestyle domain. He has experience in developing and implementing advanced analytics approaches including Statistical Modelling, Machine Learning algorithms, Natural Language Processing, Text mining, Deep Learning. He has worked on very large datasets (both structured and unstructured) and design, develop and implement R&D and pre-product prototype solutions. He can implement end to end Bigdata pipeline and perform Data analytics using cutting-edge AI technologies.

X Topic Abstract

Machine Learning and Deep Learning is evolving at rapid pace. With better support from GPU and Cloud scale infra. various possibilities with Machine Learning are becoming real. This session will focus on Key new ML/DL algorithms and their applications in AI world.

Speaker Profile

Sudhanshu (Suds) is principal data scientist with Infosys. He has more than 20+ years of experience. He is innovator, and architect of Infosys Enterprise Cognitive platform(iECP). iECP provides API for training and detection for the use cases in Computer Vision, Speech, unstructured text area and is built on principles of micro services. Sudhanshu is AI enthusiast and fascinated by possibilities it has to offer in industrialization.

X Topic Abstract

Recently, Python has become language of choice for building machine learning / deep learning systems. One of the prime reasons being its extensive set of libraries.
In this session, overview of top machine learning libraries will be covered for following aspects of the machine learning,
1. Data Manipulation - Pandas, Numpy
2. Data Visualization - Matplotlib, Seaborn, Altair
3. Machine Learning Algorithms - scikit-learn
4. Deep Learning - PyTorch, Tensorflow, Keras
5. Natural Language Processing - NLTK, Spacy
6. Reinforcement Learning - OpenAI Gym
7. Machine learning at scale - PySpark

Speaker Profile

I am currently working as senior technical consultant at SAS Research and Development Pune. With 11 plus years of experience with technology leadership and software architecture, I am passionate about bots, analytics, machine learning, reinforcement learning and deep learning, Cloud Technologies. In my free time, exploring reinforcement learning algorithms and experimenting with machine learning libraries in Python, PyTorch, and Spark/H2O.

X Topic Abstract

Machine Learning can be applied in various use cases. Here we will look at a few diverse use cases to understand its high level application.
- managing mental and physical health by monitoring speech
- Intelligent helpdesk ticketing system
- Container Behavior Analysis
- DevOps Platform
- healthcare

Speaker Profile

I am principal architect in GS Lab. I have over 23 years of experience in software industry. I have 8 US patents issued in my name. I have done B Tech from IIT Bombay and MS from Georgia Tech both in Computer Science. I am one of the mentors for machine learning foundations course of machine learning specialization on coursera. I have been conducting training sessions and hands on workshops on ML and deep learning. I have architected ML solutions for a number of GS Lab customers.

X Topic Abstract

The pervasive use of AI in several fields (driverless cars, image recognition, fraud analytics etc.) and its importance in our lives have brought a very important problem of machine learning algorithms. Traditionally, many advance classification algorithms are black box models. i.e. Though we can predict the outcome with some confidence level, we can’t explain how did algorithm arrived at a particular outcome and what is the individual weightage of each parameter. This is also why regulators and business community show reluctance to the application of machine learning algorithm in sensitive business problems such as prediction of fraudulent banking transactions and shortlisting of a candidate’s profile with machine learning.
Recently, there has been a great progress in white box machine learning algorithms, which are interpretable. i.e. we can explain the outcome of such models. I am going to explain the overview and mathematics behind few white box machine learning algorithms.

Speaker Profile

Amar is a B.Tech. graduate from IIT, Dhanbad and an MBA from XLRI Jamshedpur. He started his career from a Manufacturing company and later worked in advance production planning system consulting projects. After few years working in consulting assignments, he was naturally pulled towards data , statistics and analytics. Finally, he switched to data science 5 years back and has followed his passion since then. Amar has worked in individual contributor as well as leadership role in data science teams. In his current assignment, he is leading a team with members from three countries.

He had opportunity to work in data science projects from diverse industries such as energy, banking, manufacturing and legal. He is comfortable turning his hand to any industry and any type or size of dataset. In previous company, he implemented in fraud analytics in large banks from US and UK. In the current company, he is implementing data science across all functions such as factory of future with, supply chain analytics, marketing and finance.

Amar is passionate about contributing to data science communities.

Besides data science, he is interested in yoga and a certified yoga instructor.

X Topic Abstract

Real-world datasets, especially those involving occurrence of a rare event, such as a rare disease, is often crippled with an imbalance. This means, negative samples (non-disease occurrances in our previous example) highly outnumber positive samples (disease occurances). Most of the state-of-the-art machine learning models do not employ imbalance-aware learning, resulting in models that are not generalizable to unseen data. Through specific use cases, I will discuss the problems inherent in these models and how to go about building an imbalance-aware classification model.

Speaker Profile

Afreen Ferdoash is a Data Scientist at Persistent Systems Pvt. Ltd. She has wide knowledge and experience in Machine Learning and NLP and their application to diverse sectors such as IT Services, Healthcare, Energy and Life Sciences. Some of her key projects involve building an end-to-end Question Answering system, forecasting IT tickets volumes, predicting Hospital Acquired Infections in patients and predicting operational efficiency in HVAC systems. She has also authored several publications in the areas of Neuroscience, Energy and Healthcare.
Afreen holds a B.Tech. degree from IIT Kharagpur and a MS degree from Washington University in St. Louis.

X Topic Abstract

Digital Analytics is in general descriptive form of Analytics. This is mostly used to evaluate the KPIs of a digital asset or to quantify the success of various tests for user experience optimization. There are plenty of packages in both R as well as Python with which data from DA tools like Google Analytics and Adobe Analytics can directly be pulled into ML tools and analyzed to extract actionable insights. I will be covering one such application where in I will connect Google Analytics with R Shiny to perform a market basket analysis

X Topic Abstract

Knowledge graphs generation is outpacing the ability to intelligently use the information that they contain. Knowledge graphs have the potential to provide both a representation of the world and a technical interface that allows us to develop better AI and to turn it rapidly into useful products. In this session, Satish will deep dive to explain how Deep learning can be used in conjunction with the knowledge graph.

Our Sponsors

Use this opportunity to improve the visibility of your organization

Instant Sponsorship
Avail instant sponsorship at just USD 2000

Instant sponsorship includes
• Branding of your company as Bronze Sponsor – Company's Logo on the event page with cross link to your website.
• One Speaking Slot (45 min -non sales talk).
• 10% discount on registration fee for any delegate from your organization.
• Full day attendance at the event with lunch
• 1 x Roll up stand / Brochure distribution at the event
• Online Interview post of your company's senior executive at our media portal

For Silver, Gold Platinum & Titanium Sponsorship opportunites, please request for Sponsorship Brochure via email at contact@1point21gws.com, naveen@1point21gws.info

Our Speakers


Saket Thite

Software Architect

Pitney Bowes Software


Amar Kumar

Data Science Manager

Coats


Yogendra Joshi

Director

Oracle


Afreen Ferdoash

Data Scientist

Persistent Systems


Mo Karimkhan Pathan

Data scientist

DataMetica Solutions Private Limited


Sanmeet Walia

Founder

DataVinci Private Limited


Satish Patil

Founder and Chief Data Scientist

Crysagi Systems Pvt Ltd


Sudhanshu Hate

Senior Principal Technology Architect

Infosys Ltd.


Saurabh Deshpande

Senior Technical Consultant

SAS


Sameer Mahajan

Principal Architect

GS Lab

Want to become Speaker Please register here Register

Our Pricing

Special Offer

Rs 7000 + GST

Till January 10
Group of three or more

Rs 7500 + GST

Till February 02
Early Bird

Rs 8000 + GST

Till January 02
Standard

Rs 10000 + GST

Till February 02


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Our Testimonial

FAQs

Who can attend Machine Learning Day in Pune?

• Data Engineers/Developers / Scientists
• Analytics Professionals
• Startup Professionals
• Scientists/Researchers
• Professors
• President/Vice president
• Chairs/Directors

And last but not the least……….
Anyone interested in Machine Learning & thrives to make the future developed and better

Why to attend Machine Learning Day in Pune?

Understand the state of development of Machine learning by exchanges, clearing houses, central counter parties and payment systems, and what it means for you.

What will you learn about?

Detecting where underlying problems and frictions exist in your organisation that will be alleviated by Machine learning technologies. Using Machine learning as a tool for innovation across your organisation

Are there any prerequisites to attend this program?

No

Do I need to register for the event?

Yes, all conference attendees must register in advance to attend the event.

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Australia - +61416893630 / +61416576383

naveen@1point21gws.info

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