Ville Tuulos is a former Netflix data scientist and engineer who now helps people manage their data pipelines. He's the author of Effective Data Science Infrastructure from Manning publishing and the creator of the Metaflow system for managing data pipelines. He explains how to think about data and how to plan out how to gather, manage, and transform your data using a system like Metaflow.

The conversation starts out asking what’s coming down the pipeline for the Machine Learning community. Ben explains why it’s hard to predict and leads the conversation into what the challenges really are in Machine Learning and the movements across the field to make it more clear on how to get value from your ML setup.

In this episode, Ben, Francois and Chuck talk about the skills and knowledge that will help you get started with machine learning. Ben outlines 3 different things that will get you started faster than anything else. Francois and Chuck add a couple more things and they discuss the best ways to implement each one of these skills or tactics to become a top notch Machine Learning Engineer.

In this episode we talk with Serhii Maksymenko about how to scale video processing with DL frameworks. From buffered asynchronous processing to how to get started with projects of this complexity, Serhii discusses his project work and unique take on how to build these systems without breaking the bank.

Chuck dives into the 3 essentials for getting the next successful outcome you want in your career. Whether that's something simple like a raise or something more complex like going freelance, you can achieve it by working on 3 main areas.

Chuck dives into the 3 essentials for getting the next successful outcome you want in your career. Whether that's something simple like a raise or something more complex like going freelance, you can achieve it by working on 3 main areas.

Chuck explains what he taught Nathan last week when we asked how to get hired at a FANG (Facebook Apple/Amazon Netflix Google) company. Essentially, it boils down to how to build the skills and knowledge needed to pass the interview. How to build the relationships to get into the door and have the interviewer want you to succeed. And how to build the reputation that has the company wanting you regardless of the outcome.

Michael Galarnyk is a Developer Relations at AnyScale and has nearly 10,000 follows on Medium. He joins the adventure to walk Chuck through how he's parallelized the training of his Machine Learning models on multi-core machines. He also walks Chuck through the ins and outs of being in Developer Relations.

Derrick Mwiti joins the adventure to discuss the various tools you can use to jumpstart your Machine Learning adventure. He walks through several frameworks for Machine Learning and points out several Tensorflow extensions that will make your Machine Learning models better and your understanding of what is going on easier.

Qingquan Song is a member of the AutoKeras team and recent Phd graduate from Texas A&M University. He co-authored the Automated Machine Learning book from Manning publishing and joins the adventure to explain automated machine learning and how it can be used to set up and to refine machine learning models. He also dives into how to use the tools that exist to take advantage of the techniques it offers.

Chuck was on a strategic call with one of his potential coaching clients talking about cryptocurrencies and realized that this is one of the major reasons that people want to become influencers. Or, rather, that many people aspire to make a difference and/or make money and the best way to do that is to become the person people go to for what you do.

Annie Didier from NASA’s Jet Propulsion Lab talks to us about the Machine Learning algorithms and process that goes into how the next Mars rover will choose how it moves across the surface of Mars. She explains each algorithm and how they go together to make the decisions that the Rover makes.

Charles talks about the things that get developers stuck when they're trying to start their podcast or other influencer channel. He explains how to get around having those things hamper your journey.

Gant's back!!! He's releasing a book with Manning Publishing about Tensorflow.js and he's here to discuss all the details with us. He explains the difference between Teonsorflow and Tensorflow.js and goes into some of the pros and cons of using it. He also explains the concepts he goes over for new ML engineers and for ML engineers learning JavaScript.

Charles Max Wood talks about how to build, grow, and benefit from positive relationships within programming. He talks about how he's built genuine positive relationships with hundreds of programmers and how he and others have grown from those relationships. He also explains that you get out of relationships what you put into them. Finally, he goes into how to begin to build relationships by building a system of influence you can use on behalf of the people you want relationships with.

Miguel and Chuck discuss how to stay current in the rapidly changing world of Machine Learning and Artificial Intelligence. They go over how to pick books, newsletters, podcasts, and other resources to up your Machine Learning knowledge and skills.

Charles Max Wood discusses several opportunities that came his way early in his podcasting career and other opportunities that have come to other people after only a couple of podcast episodes. He explains why that happens and how you can use this to create more influence as a developer.

Charles Max Wood discusses several opportunities that came his way early in his podcasting career and other opportunities that have come to other people after only a couple of podcast episodes. He explains why that happens and how you can use this to create more influence as a developer.

Charles Max Wood started podcasting because it sounded fun and because he wanted to talk about technology. He learned pretty quickly that it got him access to people who understood the things he wanted to learn. The reasons changed over the years, as Charles explains before he talks about the big payoff he gets now from doing the podcasts.

Francois Bertrand is the author of a tool that builds in powerful data visualization tools for datasets that allow data scientists and machine learning engineers to look at their data and analyze various qualities that they have. This could allow engineers to make qualitative calls regarding the data they use to train their models or evaluate the results they get from models after the fact. Francois explains how he built it and how to use it for these types of uses.

Jason Weimann started out as an enthusiast of the Massively Multiplayer Online Role Playing Game, Everquest. After becoming a software developer and building a collaborative community playing the game, learn how he used his connections to get a job working for the company that made the game, even if it wasn't a job working as a game developer and how that led to a career working on one of the most popular online games of the time.

Ather Fawaz joins the discussion to walk us through the world of qubits, quantum computers, machine learning algortithms, and what quantum computer means for machine learning. He explains the basics of quantum computer and who the major players are in the space and then explains some of the advancements people are making by scheduling time on their quantum computers.

Chuck outlines how he's used his podcasts to find mentors to continue his learning journey over 12 years of podcasting. Some mentors have been long lived relationships while others have lasted only a few months or even days. This episode shares Chuck's experience learning from the top people in the development community as a programmer and podcaster.

Chuck outlines how he's used his podcasts to find mentors to continue his learning journey over 12 years of podcasting. Some mentors have been long lived relationships while others have lasted only a few months or even days. This episode shares Chuck's experience learning from the top people in the development community as a programmer and podcaster.

Ben Wilson is the author of Machine Learning in Action from Manning. He leads us through the process of compiling data, building algorithms, and learning Machine Learning.