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Published Feb 28, 2017

How to Build Confidence as an ML Developer with Siraj Raval - #2

Siraj Raval explores the journey of building confidence as a machine learning developer through practical applications and leveraging online resources, while also sharing his creative process for engaging content creation. The discussion delves into future trends such as chatbots and adversarial learning, highlighting their transformative impact on the AI landscape.
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  • Production Process

    shares his meticulous video production process, which involves several stages from research to release. He begins with in-depth research on a topic, followed by programming simple examples, technical writing, and finally, video production and editing. This entire process, which takes about 60 hours per video, is now expanding as he plans to produce two videos a week, necessitating the hiring of a technical video editor 1.

    Over time, I'm building the process. What it is, the first part is research. What is the topic? I want to talk about and let me just learn about it.

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    His journey into YouTube began as a side project while working at Twilio, driven by a passion for video documentation and a desire to improve production quality 2.

       

    Audience Engagement

    Engaging a diverse audience is a challenge that navigates by creating content for researchers, developers, and non-technical viewers. He aims to eventually have dedicated channels for each audience type, but currently, his videos cater to all three groups 3.

    I have the research scientists, the cool kids who are like developing the novel algorithms. Then there's the developers who are honestly, they're also the cool kids.

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    Curation of content involves browsing platforms like Reddit and Twitter to find trending topics that align with his interests. Despite the abundance of information, he manages to identify valuable content for his audience 4.

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