Best Sanket Gupta Podcasts (2024)

1
27: Building Open Source Data Startup with Airbyte CEO, Michel Tricot 44:55

2+ y ago44:55

44:55

We talk with Michel Tricot, who is the Founder and CEO of Airbyte, which is an open source data integration Y Combinator startup. It has raised over $30M in capital and has been growing quite fast. It was a great conversation and I think you will also enjoy it. 🎉 We cover lots of things in the podcast including: 1. Technical aspects of what Airbyte…

1
26: Building Data Engineering Pipelines at Scale (with Data Warehouse, Spark and Airflow) 39:30

3y ago39:30

39:30

Imagine you are at a beach and you are hanging out and seeing all the waves come and go and all the shells on the beach. And you get an idea. How about you collect these shells and make necklaces to sell? Well how would you go about doing this? Maybe you’d collect a few shells and make a small necklace and try to show to your friend. This is where …

1
25: Talking Data Privacy with Jeff Bermant 28:11

3y ago28:11

28:11

In this episode, I'm excited to be talking with Jeff Bermant, who is the founder and CEO of Cocoon Mydata Rewards browser. It is a browser based off Chrome and it pays people to use it! ✨ In this episode we talk about data ethics and privacy, and how Jeff believes that users should be paid for their data. We talk about GDPR and similar laws in US, …

1
24: Promoting Women in Tech - With Rupal Gupta 15:05

3+ y ago15:05

15:05

In this episode, we are talking about women in tech with Rupal Gupta. Rupal, a recent graduate from Online MS in CS from Georgia Tech, is a data engineer in the industry and is passionate to help promote women in tech. She also has some great tips and resources for anyone trying to break into data science and tech! In this episode we talk about thi…

1
23: Let’s Talk AWS SageMaker for ML Model Deployment 19:46

4y ago19:46

19:46

In this episode, we talk about Amazon SageMaker and how it can help with ML model development including model building, training and deployment. We cover 3 advantages in each of these 3 areas. We cover points such as:1. Host ML endpoints for deploying models to thousands or millions of users.2. Saving costs for model training using SageMaker.3. Use…

1
22: Transfer Learning for NLP - With Paul Azunre 46:46

4y ago46:46

46:46

In this episode, we are talking with Paul Azunre. Paul is one of the world’s experts in the area of Transfer Learning for NLP and is also an author of the upcoming book Transfer Learning for NLP published by Manning Publications. In this episode we talk about things such as: 1) Paul’s background and how his background in maths and optimization as w…

1
21: Why Scikit-Learn and Keras are Awesome for ML 19:54

4+ y ago19:54

19:54

In this episode, we talk about why the two libraries Scikit-Learn and Keras are great for machine learning. These two libraries combined with Pandas form the 3 core libraries in Python for a data scientist today. We cover things like: 1) Data Exploration and data cleaning - how Pandas and Jupyter notebooks provide a good way to get started here. 2)…

1
20: Yogi's Guide to Analytics - An Interview with Akshay Kanade 35:44

4+ y ago35:44

35:44

In this episode, we talk with Akshay Kanade. He is a business analyst working in New York City who likes taking a big view of data, and has very interesting spiritual views on data analytics and life in general, he is also a handwriting expert- he can read people’s handwriting and can recognize a lot about their personalities. In this interview we …

1
19: Statistics and Data Science- An Interview with Patrick McClory 56:20

4+ y ago56:20

56:20

In this podcast episode, we do an interview! We talk with Patrick McClory, who is the founder and CEO of IntrospectData. He is an expert working in areas of data science consulting, large machine learning projects, math, statistics and more.In this episode we cover several interesting topics such as:1) What makes a good data scientist?2) The differ…

1
18: 5 Things to Consider for Master of Science (MS) in US 19:00

4+ y ago19:00

19:00

What should you consider for pursuing MS in US? There might be several questions in your mind as you explore this question. In this episode we cover some of the main things to consider before you make the decision. I also go into details about things which I wish I knew before coming to US for MS. The things I cover in the podcast are to consider f…

1
17: Why Pandas is the new Excel 16:37

4+ y ago16:37

16:37

The Data Life Podcast is a podcast where we talk all-about real life experiences with data and data science science tools, techniques, models and personalities. In this episode, we will talk about how Pandas is becoming a tool of choice for many data scientists for doing their data analysis work. We will explore how Pandas wins over Excel in severa…

1
16: Getting Started with Natural Language Processing 19:31

4+ y ago19:31

19:31

So many tweets and news articles and unstructured text surrounds us. How do we make sense of all of these? Natural language processing or NLP can help. NLP refers to algorithms that process, understand and generate aspects of natural language either in text or in spoken voice. In this episode we will cover some of the common techniques in NLP to he…

1
15: Using Flask, REST API and Vue.js to build a Single Page Web Application 20:39

5y ago20:39

20:39

As a data scientist, you will work on machine learning models that are deployed on websites - usually wrapped around a REST API, these days they also call this approach a “micro-service”. It is for this reason it is important to know how backends and front ends work and how to build them. In this episode, we talk about building a note app which is …

1
14: Building a Character-Based Text Classifier 23:20

5y ago23:20

23:20

Ever wonder how to automatically detect language from a script? How does Google do it? Ever wonder how Amazon knows whether you are searching for a product or a SKU on its search bar? We look into character-based text classifiers in this episode. We cover 2 types of models. First is the bag-of-words models such as Naive Bayes, logistic regression a…

1
13: Statistics of A/B Testing 21:22

5y ago21:22

21:22

You and your team might spend a lot of time building a new feature. But how do you know if this feature will be liked by the users? One of the ways to statistically prove this is by using A/B testing. Listen to this episode to get tips, tricks and intuition behind hypothesis testing, alpha, beta, p-values, two-sample t-tests and more. These underst…

1
12: Your Users Don't Care How Smart You Are 5:04

5y ago5:04

5:04

In this episode, we will talk about the importance of business impact in data science. "Your users don't care how smart you are" was a quote I read that got me started in thinking about this. The right way to do data science is to think of users, revenue impact, business value and go for the simplest solution possible. The wrong way to do data scie…

1
11: The Ten Essential Machine Learning Questions 19:08

5y ago19:08

19:08

This episode covers the ten essential machine learning questions. Disclaimer: Baseline answers have been provided in the episode for guidance. For complete accuracy, please refer to textbooks or to courses by Andrew Ng on Coursera. If this content is useful, please consider buying me a coffee via the link https://anchor.fm/the-data-life-podcast/sup…

1
Mining Twitter Data for Sentiment Analysis of Events 18:43

5y ago18:43

18:43

Twitter is a rich source of live information. Is it possible to run sentiment analysis on what the world is thinking as an event unfolds over time? Could we track Twitter data and see if it correlates to news that affects stock market movements? These are some of the questions that we will answer in this podcast episode. There are 6 steps for minin…

1
Don't Be Shy To Pursue Your Interest 5:00

5y ago5:00

5:00

In this episode, we will talk about things like Maslow's Hierarchy of Needs, and focussing on higher level needs such as satisfaction and achieving full potential. In the area of tech, data science and software development, admitting your interest could involve "shyness" as the next shiny cool thing is pursued by everyone. But if your interest is i…

1
Review of Udacity Nanodegrees - are they worth it? 13:03

5y ago13:03

13:03

Udacity has become a popular platform for learning about various things in data science, machine learning and programming in general. In this episode, we will discuss the good, bad and ugly of the Udacity nanodegrees. I will also cover my experiences with Deep Learning and NLP Nanodegrees. We will cover things like how Udacity has great production …

1
6 Steps to Transition to Data Science from non-CS background 15:58

5y ago15:58

15:58

In this episode we will talk all about the various steps to transition to data science from non computer science backgrounds. One of the main difficulties people face from non-CS backgrounds is how overwhelming it can be to transition to data science field, I talk about my own journey, and share the 6 steps which can help you in your own data scien…

1
The Top 5 Data Science Podcasts 8:20

5y ago8:20

8:20

Welcome! In this episode, we will cover some of the top data science podcasts, that have helped me a lot in my own journey, and hopefully will be helpful to you as well. The top 5 podcasts are (linked to my favorite episodes):1) AI in Industry with Daniel Faggella2) This week in Machine Learning and AI (TWiML)3) DataFramed4) Data Skeptic5) Talk Pyt…

1
What I learnt building a data science course 18:16

5y ago18:16

18:16

Have you ever thought about building a video course? Have you wanted to share your expertise with other people via a video course on different platforms like Udemy? Have you wondered what are the economics and revenue details of building a course? This podcast episode is for you! In this episode, I talk about my experience in building my first data…

1
Overview of Netflix and Spotify like recommendation engines 13:28

5+ y ago13:28

13:28

In this episode, we cover the two main types of recommendation engines used at companies like Netflix and Spotify. 1) Content based recommendation systems use the genres or tags of each product to find other similar products to recommend to users. 2) Collaborative filtering based recommendation systems use user activity and user ratings on the webs…

1
3 Mistakes to Avoid in a Machine Learning Project 10:18

5+ y ago10:18

10:18

You and your team might spend weeks or even months building a model. These are the 3 mistakes to avoid in your next machine learning project! This can save you a lot of time and effort in your next project. These tips have been learnt from experiences deploying ML models in production as well as hearing from experts in the field. These tips and mis…

1
Flask is a Great Tool for Full Stack Data Science 10:43

5+ y ago10:43

10:43

In this episode, we will talk all about what makes Flask such a great tool for both beginner and experienced data scientists to know. It was one of the first tools I learnt in my data science journey, and it has been so useful along the way. Flask is a micro-framework in Python which allows to build websites in a simple way. Flask will make you as …

1
Hello, World! 1:59

5+ y ago1:59

1:59

To kick things off, I talk about the kind of topics you can expect to hear in this podcast. Welcome to The Data Life! --- Send in a voice message: https://podcasters.spotify.com/pod/show/the-data-life-podcast/messageSupport this podcast: https://podcasters.spotify.com/pod/show/the-data-life-podcast/support…

Podcasts Worth a Listen

Sanket Gupta Podcasts

Podcasts Worth a Listen

1
The Data Life Podcast

Sanket Gupta

1
27: Building Open Source Data Startup with Airbyte CEO, Michel Tricot 44:55

1
26: Building Data Engineering Pipelines at Scale (with Data Warehouse, Spark and Airflow) 39:30

1
25: Talking Data Privacy with Jeff Bermant 28:11

1
24: Promoting Women in Tech - With Rupal Gupta 15:05

1
23: Let’s Talk AWS SageMaker for ML Model Deployment 19:46

1
22: Transfer Learning for NLP - With Paul Azunre 46:46

1
21: Why Scikit-Learn and Keras are Awesome for ML 19:54

1
20: Yogi's Guide to Analytics - An Interview with Akshay Kanade 35:44

1
19: Statistics and Data Science- An Interview with Patrick McClory 56:20

1
18: 5 Things to Consider for Master of Science (MS) in US 19:00

1
17: Why Pandas is the new Excel 16:37

1
16: Getting Started with Natural Language Processing 19:31

1
15: Using Flask, REST API and Vue.js to build a Single Page Web Application 20:39

1
14: Building a Character-Based Text Classifier 23:20

1
13: Statistics of A/B Testing 21:22

1
12: Your Users Don't Care How Smart You Are 5:04

1
11: The Ten Essential Machine Learning Questions 19:08

1
Mining Twitter Data for Sentiment Analysis of Events 18:43

1
Don't Be Shy To Pursue Your Interest 5:00

1
Review of Udacity Nanodegrees - are they worth it? 13:03

1
6 Steps to Transition to Data Science from non-CS background 15:58

1
The Top 5 Data Science Podcasts 8:20

1
What I learnt building a data science course 18:16

1
Overview of Netflix and Spotify like recommendation engines 13:28

1
3 Mistakes to Avoid in a Machine Learning Project 10:18

1
Flask is a Great Tool for Full Stack Data Science 10:43

1
Hello, World! 1:59

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