What we're about

1. This meetup group is for people who want to begin their careers in the Data Science field.

2. Data science lovers

3. Connect people with data experts in different areas.

Upcoming events (4)


Online event


We are happy to announce our new full-stack data science bootcamp starting September 18th. This is another great opportunity to start a data science career. The program is to prepare you for a data scientist position. Our program is the best quality bootcamp offering more live-interactive time with top notch mentors/instructors and well-designed projects. We have a special early bird discount till August 15th. We have limited capacity for this upcoming batch (first come-first serve).

The bootcamp will teach you Python, SQL, Research Design, Exploratory Analysis, Machine Learning, NLP, Apache Spark Basics, and hands-on projects. During our program, you will explore a hands-on experience that will ignite your enthusiasm and boost your confidence to learn data science which will help you land a well-paid job.

All successful participants who attend more than 80% of the course will be granted a graduation certificate and become Magnimind alumni. What You’ll Learn in these 15 weeks?

- SQL, Python
- Math and Statistics for Data Science
- Fundamentals of Machine Learning
- Natural Language Processing
- Big data and Cloud
- Hands on projects
- Career support, Practice Interviews and Landing a Job Phase


Objectives of our programs:
-Provide hands-on skills and fundamental data science training
-Allow students to engage with multiple talented mentors and instructors
-Expose students to industry-standard projects
-Connect with engineers and scientists in Silicon Valley
-Teach students interview skills and provide coaching

Why to choose Magnimind bootcamps?

-We have the best quality education with the most affordable price among all bootcamps.
-We offer four times more live-interactive mentor/instructor time compared to other major bootcamps.
-Our mentors are both from industry and academics which will provide your strong theoretical and practical skills.
-Lifetime access to large and ever-enriching advanced and diverse data science content and to our network of top-notch scientists and engineers from Silicon Valley.
-Projects are well-designed to address industry needs and to acquire essential skill sets for landing a job.

If you would like to enroll in this program, you have several payment options:

- A super early bird discount (%65) if tuition is paid in full upfront ($2,100 instead of the full $6,000, saving you $3,900).

-We offer an income share agreement (ISA), which lets you defer payment until you are employed. You will pay the full $6,000 amount but take the defer payment opportunity.

The road to your future career starts today!

Program Start Date: Sept 18


Building The Data Lakehouse

Online event

First there were applications. Then there were data warehouses. Then people found they could start to include text into their decision making process. Next analog/IoT data appeared and there were data lakes and data scientists. Out of this miasma comes the data lakehouse. The data lakehouse incorporates different kinds of data and provides an infrastructure for the data scientist, the business analyst and the business owner to have insight into their data like never before. The data lakehouse gives new meaning to the term “data driven”.

This presentation discusses the origins of the data lakehouse, the architectural structure of the data lakehouse, and the challenges and the opportunities presented by the data lakehouse.


11:45 am - 11:50 am Arrival and socializing
11:50 am - 11:55 am Opening
12:00 pm - 1:50 pm Bill Inmon, "Building The Data Lakehouse"
1:50 pm - 2:00 pm Q&A

About Bill Inmon

Bill Inmon – the father of the data warehouse, has written 62 books and sold over a million copies worldwide. Bill’s books have been translated into 9 languages. One book Bill wrote has sold over 500,000 copies. Bill was named by ComputerWorld magazine as one of the ten people who most influenced the first 40 years of the computer profession.

Bill’s latest book coming out in October is BUILDING THE DATA LAKEHOUSE, Technics Publications, New Jersey. Bill resides in Denver, Colorado.

Please register using the zoom link to get a reminder:


Webinar ID:[masked]

Cloud Microservices for the next Billion People

Online event

The food wastage in India is 70 tonnes per year, and there is mismanagement at several layers. Approximately 20-30% of the wastage happens in the last mile, between wholesale traders, and retail mom-and-pop stores. Is there something we can do about food wastage?
This was the problem statement I attempted to solve as a first engineering hire at a startup. Our customers were 12.8 million retail owners that deal in FMCG (Fast-moving consumer goods, such as food grains, tooth paste, etc.). The goal was to develop a platform for retail traders (mom and pop shop owners / small and medium business owners) to buy FMCG products from wholesale traders using an Android app.
We were attacking a deeply entrenched business practice to help solve a societal goal. For a section of the population which is not very well versed with smartphones and technology, the user experience had to be designed from the ground up to be multi-lingual, fungible, unstructured, and relevant. In this talk, I cover how we went about iterating the solution from a simple SMS based system to a full fledged app backed by micro-services. Having a micro-service architecture provided us the agility to experiment and iterate quickly, and we were able to push out changes much faster, and help solve wastage problems even sooner.
I will discuss the several problems we faced in this segment with regards to unstructured data, and how our data models had to adapt. We used cloud services extensively, so I will also cover how different pieces came together in a cogent form to build better experience for our customers.

After having worked in bigger companies on software projects that scale to millions of devices, this was a unique challenge for me, and something I am very proud of. I would like to share my experience in building empathetic software for the masses.


4:55 pm - 5:00 pm Arrival and socializing
5:00 pm - 5:05 pm Opening
5:05 pm - 6:50 pm Tejas Chopra, " Cloud Microservices for the next Billion People"
6:50 pm - 7:00 pm Q&A

About Tejas Chopra

Tejas Chopra is a Senior Software Engineer, working in the Data Storage Platform team at Netflix, where he is responsible for architecting storage solutions to support Netflix Studios and Netflix Streaming Platform. Prior to Netflix, Tejas was working on designing and implementing the storage infrastructure at Box, Inc. to support a cloud content management platform that scales to petabytes of storage & millions of users. Tejas has worked on distributed file systems & backend architectures, both in on-premise and cloud environments as part of several startups in his career. Tejas is an International Keynote Speaker and periodically conducts seminars on Micro services, NFTs, Software Development & Cloud Computing and has a Masters Degree in Electrical & Computer Engineering from Carnegie Mellon University, with a specialization in Computer Systems.

Please register using the zoom link to get a reminder:


Meeting ID:[masked]

Deep Embeddings and Section Fusion for Music Segmentation

Please register using the zoom link to get a reminder:


Music segmentation algorithms identify the structure of a music recording by automatically dividing it into sections and determining which sections repeat and when.

In this talk I give an overview of this music information retrieval problem and present a novel music segmentation method that leverages deep audio embeddings learned via other tasks.

This approach builds on an existing segmentation algorithm replacing manually engineered features with deep embeddings learned through audio classification problems where data are abundant. Additionally, I present a novel section fusion algorithm that leverages the segmentation with multiple hierarchical levels to consolidate short segments at each level in a way that is consistent with the segmentations at lower levels.

Through a series of experiments and audio examples I show that this method yields state-of-the-art results in most metrics and most popular publicly available datasets.


11:45 am - 11:55 am Arrival, socializing and Opening
11:55 am - 1:00 pm Oriol Nieto, "Deep Embeddings and Section Fusion for Music Segmentation"
1:00 pm - 1:10 pm Q&A

About Oriol Nieto:

Oriol Nieto (he/him or they/them) is a Senior Audio Research Engineer at Adobe Research in San Francisco. He previously was a Staff Scientist in the Radio and Music Informatics team at Pandora, and holds a PhD from the Music and Audio Research Laboratory of New York University. His research focuses on topics such as music information retrieval, large scale recommendation systems, music generation, and machine learning on audio with especial emphasis on deep architectures. His PhD thesis is about trying to better teach computers at “understanding” the structure of music. Oriol develops open source Python packages, plays guitar, violin, cajón, and sings (and screams) in their spare time.

Please register using the zoom link to get a reminder:


Webinar ID:[masked]

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