Ran this quickly on that image: === Low Detail === The books are partially obscured, but I'll list the titles that I can read or identify: 1. "Mapping Hacks" by Schuyler Erle, Rich Gibson, Jo Walsh
2. "Programming Hacks" (full title and authors not visible)
3. "The Return of
CODE
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Identifying Programming and Mapping Technical Books Collection
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Perplexity Labs Introduces Gemma 2B and 7B Models
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Introducing new additions to Perplexity Labs: Experience Gemma 2B and 7B models known for impressive performance despite being lightweight. Try it now on https://t.co/2yYQB9jln7. pic.twitter.com/PIipmESdXN
— Perplexity (@perplexity_ai) 21 février 2024Introducing new additions to Perplexity Labs: Experience Gemma 2B and 7B models known for impressive performance despite being lightweight. Try it now on http://
labs.pplx.ai. -
101 Data Science Cheat Sheets for ML DL and Programming
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101 #DataScience Cheat Sheets for #DataScientists and other #coding / #algorithm / data lovers (#MachineLearning, #DeepLearning, Scraping, #Python, R / #Rstats, #SQL, #Mathematics & #Statistics): https://
medium.com/@anushka.datas
coop/101-data-science-cheat-sheets-ml-dl-scraping-python-r-sql-maths-statistics-ef30b4d786eb
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Technical Accessibility: The Impact of Video Demonstrations
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# on technical accessibility One interesting observation I think back to often:
– when I first published the micrograd repo, it got some traction on GitHub but then somewhat stagnated and it didn't seem that people cared much.
– then I made the video building it from scratch, -
IBM WatsonX Foundation Models LangChain Integration for Business
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@IBM WatsonX Foundation Models for Business Dive into IBM WatsonX's powerful foundation models with our LangChain integration! Leverage WatsonX's AI and data platform, built specifically for business applications. Begin your journey today with the `langchain-ibm` python
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Machine Learning with Python for Everyone Book Guide
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#MachineLearning with #Python for Everyone: http://
amzn.to/43HEaFS
(part of the Data & Analytics Series from Addison–Wesley Publishers)
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#ML #DataScience #AI #DeepLearning #BigData #DataScientists #Coding -
Hands-On Introduction to Machine Learning Fundamentals
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Hands-On Introduction to #MachineLearning: https://
amzn.to/497o4bP ————
#NeuralNetworks #BigData #Analytics #DataScience #DataScientists #AI #DeepLearning #Coding #Rstats #Python #ML -
Data-Centric Machine Learning with Python: Engineering Quality Models
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Data-Centric #MachineLearning with #Python: The ultimate guide to engineering and deploying high-quality models based on good data To be released in March. Place your order here: https://
amzn.to/3UC1R0Q #DataScience #DataScientists #AI #Coding #DataFluency #DataStrategy #CDO -
Kaggle Workbook: Self-Learning Exercises Data Science
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the companion book: “The #Kaggle Workbook: Self-Learning Exercises and Valuable Insights for @Kaggle #DataScience Competitions": http://
amzn.to/41jKa7r by @tng_konrad and @LucaMassaron ——————
#BigData #DataScientists #AI #DeepLearning #ML #MachineLearning #Python #Coding -
Deep dive into Gemma tokenizer and SentencePiece implementation
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Seeing as I published my Tokenizer video yesterday, I thought it could be fun to take a deepdive into the Gemma tokenizer. First, the Gemma technical report [pdf]: https://
storage.googleapis.com/deepmind-media
/gemma/gemma-report.pdf
… says: "We use a subset of the SentencePiece tokenizer (Kudo and Richardson, 2018) of