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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MACHINE LEARNING
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TinyML Applications: Keyword Spotting, Wake Words, Gesture Recognition
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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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Free Harvard Resources for Programming Data Science Machine Learning
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Don't pay ridiculous amounts of money to study Programming, Data Science, and Machine Learning. Learn these for FREE from the experts at Harvard university. (A thread)
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AI Limitations: Humans Still Essential for Quality Output
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Here are some key points from the space: 1. AI can't completely replace humans in its current implementation. 2. AI can give you a skeleton to solve a problem but specifics need to filled by humans. 3. Quality of output for these tools totally depends on the quality of input.
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Will Generative AI Replace Developer Jobs? Impact Analysis
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Will AI replace developer jobs? Amazing twitter space by @ykdojo on how generative AI like GPT-3, ChatGPT will change the landscape for developer jobs.
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Curriculum Learning and Dropout Improve Model Performance
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Thanks to using a form of curriculum learning (5 epochs) and better dropout (20 & 50 epochs) I've now been knocked off the leaderboard entirely! Here's the latest:
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AI Chatbot Generates Python Code for UMAP Visualization of Handwritten Digits
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Using Poe Sage (GPT-3.5 chatbot from @Quora
) to ask a fast-talkin' wise guy from a 1940s gangster movie how to use UMAP to visualize the topological manifold of UCI ML handwritten digits. "Snazzy" Python code and Matplotlib plot shown in reply. https://
poe.quora.com/s/kjbVTU3hH7mL
b82H1L6S
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Discussion on GPT-3 Tokenization and Spacing
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Just search “GPT-3 tokenization”. It hasn’t changed since GPT-2 days, I don’t think. I just used dashes because you need spaces to be spaces between words.
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LLM Tokenization: Not Vectors or Letters, but Token Sequences
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It doesn’t see words as embedded vectors or as letters, it sees them as token sequences — chunks of about 4 letters from a fixed mapping of strings to tokens. It does better on letter-based tasks if you ask it to first rewrite words l-i-k-e t-h-i-s.