Celebrating 13k followers Thank you for the overwhelming love and support I simplify Machine Learning, NLP, and Large Language Models like GPT-3 for you! Follow me → @Saboo_Shubham_
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Developer’s Commitment: Daily GitHub Contributions
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GF: You have commitment issues.
BF: What are you talking about?? I commit everyday on GitHub!! -
Getting Started Building Your Own AI Applications
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Good enough to get started and build your own applications.
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Excel Resources and Professional Tools Importance
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Very well summarized the importance of Excel. Great share Pauline 🙂 For more Excel resources, check out
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TensorFlow Lite for Microcontrollers: Deploy TinyML Models
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7. Deploying TinyML Learn to program in TensorFlow Lite for microcontrollers so that you can write the code, and deploy your model to your very own tiny microcontroller. https://
pll.harvard.edu/course/deployi
ng-tinyml?delta=0
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TinyML Applications: Keyword Spotting, Wake Words, Gesture Recognition
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6. Applications of TinyML You will see examples of TinyML applications, and learn first-hand how to train these models for tiny applications such as keyword spotting, visual wake words, and gesture recognition. https://
pll.harvard.edu/course/applica
tions-tinyml?delta=0
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Fundamentals of TinyML: Harvard Course on Embedded Machine Learning
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5. Fundamentals of TinyML Focusing on the basics of machine learning and embedded systems, such as smartphones, this course will introduce you to the “language” of TinyML. https://
pll.harvard.edu/course/fundame
ntals-tinyml?delta=0
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Reproducible Data Science: Statistical and Computational Tools
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4. Principles, Statistical and Computational Tools for Reproducible Data Science Learn skills to ensure you can trust your own research results, reproduce them yourself, and communicate them to others. https://
pll.harvard.edu/course/princip
les-statistical-and-computational-tools-reproducible-data-science?delta=3
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Harvard Probability Course: Essential Data Science Foundations
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3. Introduction to Probability Learn probability, an essential language and set of tools for understanding data, randomness, and uncertainty. https://
pll.harvard.edu/course/introdu
ction-probability-edx?delta=2
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Harvard’s CS50 Scratch Programming Course Introduction
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2. CS50's Introduction to Programming with Scratch A gentle introduction to programming that prepares you for subsequent courses in coding. https://
pll.harvard.edu/course/cs50s-i
ntroduction-programming-scratch?delta=0
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