Stay ConnectedMachine Learning is growing in leaps and bounds both in capability and adoption. Listen to our experts discuss the ideas and fundamentals needed to succeed as a Machine Learning Engineer.
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Copyright: © 2022 Intentional Excellence Productions, LLC
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. First, building skills. The most obvious type of skills you'll need is technical skills. However, don't neglect your people skills and your organizational skills as well since you're often paid for how you work with people and enhance their work and how you put your work together in the most efficient ways. Second, building relationships. Often other people will be able to help you find the opportunities or will be the ones to make the decisions that impact your ability to get the outcome you want. Having good relationships is key to having good outcomes. Third, building recognition. Being known for being valuable in important ways allows you to leverage the skills you have to build better relationships and create opportunities to get what you need to get the outcomes you want by giving people what they want. A podcast is a great way to do all three. Chuck explains exactly how that works in this podcast and goes deeper as part of the Dev Influencers Accelerator. Panel
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.
This approach also works for speaking at conferences, selling courses, and other outcomes as well as it's the core of building a successful career as an influencer. Panel
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. Panel
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. He and Chuck walk through each one and highlight when and why you'd want to use them. Panel
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. Panel
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. So, how do you become the first person people think of when they think of that thing you know how to do? Let Chuck tell you. Panel
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. Panel
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. Panel
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. Panel
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. Panel
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