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Welcome to the Preset Podcast, the home of "Analytics Everywhere" and "Designated Driver". Analytics Everywhere discusses wide-ranging topics in business intelligence and data engineering, and Designated Driver is a great way to get to know the database platforms of the world over a beer. These podcasts are dedicated to explore next-generation data tools and the impact they have on data teams.
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This is a podcast where we talk all-about real life experiences of dealing with data and machine learning tools, techniques and personalities. We cover not just the technical aspects but also the "life" aspects of working in the field. Note: Opinions expressed are my own and do not express the views or opinions of my employer. Support this podcast: https://podcasters.spotify.com/pod/show/the-data-life-podcast/support
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Today Max and Evan are joined by Tarush Aggarwal, CEO of 5X, as we discuss the intersection of data teams with the modern data stack, and how these tools went from a monolith model to a sea of disconnected tools and patterns. Where is this headed, and how can data teams be most effective in this new ecosystem?…
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Welcome to this episode of the Analytics Everywhere podcast! In episode #6, Max chats with Byron Allen, the ML Practice Lead at Contino. In this episode, we chat about a variety of topics around the challenges of operationalizing data: - organizational difficulties around data (data mesh vs centralized data warehouse / governance) - what a semantic…
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Welcome to this live episode of the Analytics Everywhere podcast! In episode #4, Max chats with Michel Tricot, the co-founder and CEO of Airbyte. In this episode, we talk about the challenges of data integration, the importance of establishing protocols for data connectors, how traditional REST API's fall short when it comes to data exhaust, the or…
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Welcome to this live episode of the Analytics Everywhere podcast! In episode #4, Max chats with dbt co-founder Drew Banin about the the history of dbt, Airflow vs the dbt view of data engineering, the dbt semantic layer, and more. We hope you enjoy this episode! Links: Drew Banin: https://www.linkedin.com/in/drewbanin Preset: https://preset.io/prod…
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Welcome to this live episode of the Analytics Everywhere podcast! In episode #3, Max chats with Zach Wilson from Airbnb about building data products. They talk about some of the data engineering patterns they witnessed at both small and large tech companies, data applications, and more. We end this episode with some great Q&A from the audience. -- …
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In this episode, we sit down with Pavel Tiunov, the CTO of Cube. Cube is a headless BI platform that seeks to be the serving layer for interactive analytics applications. Cube’s story is pretty interesting, because they started out as a different company with a different name before pivoting completely. This conversation is all about headless BI, a…
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Welcome to the Analytics Everywhere podcast, presented by Preset (the experts of Apache Superset). This podcast is dedicated to understanding the perspectives of the builders of next generation data tools and the impact those tools seek to have on the end user analytics experience. In episode 1, Max and Srini from Preset speak with Chris Riccomini …
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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…
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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 …
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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, …
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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…
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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…
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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…
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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)…
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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 …
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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…
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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…
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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…
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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…
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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 …
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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…
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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…
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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…
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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…
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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…
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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…
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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 …
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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…
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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…
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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…
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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…
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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…
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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 …
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Projet terminé: Jul Hat en madelinetosh DK coloris Coquette http://www.ravelry.com/projects/CocotteKnits/jul-hat le pull Sur un nuage en Drops Kidsilk et baby alpaca et silk http://www.ravelry.com/projects/CocotteKnits/sur-un-nuage (toutes les modifications détaillées son sur cette page projet Ravelry) Projets en cours: Flaum en De rerum natura et …
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Projet terminé: second châle Masgot http://www.ravelry.com/projects/CocotteKnits/masgot-2 Projets en cours: Good vibes shawl http://www.ravelry.com/patterns/library/good-vibes en laine Uncommon Thread en everyday singles coloris Ripe Plum et en La Bien Aimée Mérino single coloris Dogwood Graffiti. Akene http://www.ravelry.com/projects/CocotteKnits/…
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Projet terminé: Lothian de Justyna Lorkowska http://www.ravelry.com/projects/CocotteKnits/lothian Pure Joy de Joji Locatelli http://www.ravelry.com/projects/CocotteKnits/pure-joy Projets en cours: second châle Masgot http://www.ravelry.com/projects/CocotteKnits/masgot-2 Square and stripe http://www.ravelry.com/projects/CocotteKnits/square-and-strip…
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