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Let’s admit that we all love weekends—time to meet new people, learn new things and do things that you love. So one Sunday in August, we decided to explore the world of machine learning (ML) with the young Humans of Data, including college students and machine learning enthusiasts. 

We had so much fun hosting the Introduction to Machine Learning event, in collaboration with GDG Cloud and Women Techmakers Delhi. And of course, there was pizza and some super cool swag! 

Here’s a quick recap of the event and links to the resources shared by the amazing speakers.

Basics of ML

By Shreya Pandey

As it was a beginner-friendly event, the day started with Shreya introducing the attendees to the world of machine learning. Shreya, a student at the Delhi College of Engineering, explained that machine learning helps computer programs access data and learn, without much human intervention or programming.

Her session covered the following:

  • Difference between machine learning and programming
  • Relationship between deep learning, machine learning and artificial intelligence (Cheat code: deep learning is a subset of machine learning, which is a subset of artificial intelligence)
  • Working knowledge of machine learning and basic terminology
  • Regression vs classification 

If you are interested in learning more, you can check out the slides from the session here.

Understanding ML Application in HR Analytics 

By Jitendra Gaur

Jitendra Gaur, a Data Scientist at IBM, shared his insights and experience of applying machine learning models in HR analytics. He also shared the most common data problems faced by people working on machine learning. And, they were oh so relatable! 

Machine Learning from the Ground Up on Google Cloud Platform 

By Vaibhav Srivastav

We deal with vast amounts of data every single day! And on top of this, the data is often in different formats (mostly non-usable). But what makes data beautiful are the patterns! And machine learning involves teaching a computer to recognize those patterns.

The session by Vaibhav, a Data Scientist at Deloitte Consulting, involved learning about machine learning in detail and applying ML principles while working on Google Cloud Platform (GCP). The session covered the following:

  • Basics and use cases of ML
  • Three categories of ML
  • ML output
  • Regression and classification
  • Probability estimation
  • ML activity on GCP

If you are interested in learning more, do check out the slides from his session here, and follow Vaibhav on Twitter via @reach_vb.

Introduction to Deep Vision in Keras

By Prakhar Srivastava 

Remember how we were taught in school that the body is a machine? In his talk, Prakhar Srivastava, an ML Engineer at Atlan, shared an analogy comparing everything we see to training data and everything we infer to target output. Interesting, right? Eyes are *clearly* the best machines (pun intended), and vision is the learning process!

The session further covered how a linear machine fails when it comes to vision. Wondering why? Because a linear machine is only capable of interpreting one dimension! So to detect multiple dimensions in learning, deep learning in computer vision comes into the picture. In this session, Prakhar used Keras to explore deep learning and its applications in computer vision.

If this was enough to make you interested in the holy grail of computer vision, here are three things from Prakhar’s session for your curious mind to explore:

  • The Cambrian explosion
  • The evolution of the human eye
  • The interesting debate of vision vs language

You can check out slides from Prakhar’s session here and reach out to him on Twitter via @prakharcode.

Natural Language Processing: Making a Machine Read

By Kautuk Kundan

If you write regularly on the web, chances are you use the Grammarly app to check grammar. Or if you enjoy reading texts originally written in different languages, you probably use Google Translator. These are just some uber-awesome examples of the applications of NLP or Natural Language Processing. As the name indicates, NLP uses computational techniques to process, analyze and understand natural languages and speech. 

During his session, Kautuk, a Google MLCC Facilitator, explained the basics of NLP and its applications in today’s world. His session covered the following:

  • Basics of NLP and its applications
  • Basic terminology
  • Stemming vs lemmatization
  • ML pipeline
  • Common NLP techniques
  • Sample code

If you’ve been looking to get started with NLP, you can check out the slides from his session here. You can also reach out to Kautuk on Twitter via @Kautukkundan.

Tweet About It or It Never Happened!

We absolutely enjoyed hosting the event, bringing together young, curious minds of the humans of data. And the love on Twitter makes us think that our community loved the event just as much as we did! 

Sad about missing out on all the awesomeness from this event? Stay updated on future events by subscribing to our fortnightly Humans of Data newsletter! Sign up here.

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Author

Works on things around Talent, Growth, and Community at Atlan and tweets at @leenasoni_.

2 Comments

  1. Aeshna Gupta Reply

    Is there any procedure to join this team of professionals or to be a part of the community?

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