Ekrem Aksoy joins the adventure to discuss transformers and the method of helping Machine Learning algorithms focus on the important parts of an image to determine what to do.

Ben Wilson explains the recent developments at DataBricks with their Machine Learning mentorship program for some of their experts. He talks about his approach to helping the Data Scientists and Developers he's mentoring to understand Machine Learning more deeply and gives advice on how others could and should drive their career forward with Machine Learning.

Laszlo Sragner joins the adventure to discuss how to make your machine learning approach production ready. The discussion ranges through code quality and how to build and manage your models to keep them production ready and delivering the outcomes you're looking for.

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.