I usually read the experimental details and then straight up dive into the code.
Pick it apart till I’m down to bare metal. Create dummy tensors and then play around with individual modules to understand what is happening. Colabs are helpful here too, to isolate the code.
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Learning ML by Dissecting Code and Dummy Tensors
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Evolution of Human-Computer Interfaces: From Punch Cards to Natural Language
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oh that wasn’t very clear—i meant the evolution of how we use computers,from punch cards to command lines to higher-level programming to GUIs to touch interfaces to programming in natural language
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Automatic Pydantic Model Construction from Function Signatures
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we inspect the function signature, and use that to construct a pydantic model automatically
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Pydantic validates tool inputs easily
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pydantic allows us to add validation to tool inputs easily
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Introduction to Algorithms Third Edition Book Recommendation
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Introduction to #Algorithms (3rd edition): http://
amzn.to/3LsfrwT (over 1700 five-star reviews)
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#Mathematics #ComputerScience #100DaysOfCode #DataScience #MachineLearning #AI #Statistics #ComputationalScience -
Agent-Based Modelling and GIS: Practical Guide to Geospatial Analytics
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"Agent-Based Modelling and Geographical Information Systems: A Practical Primer (#GeoSpatial Analytics and #GIS)" http://
amzn.to/3b26CK9
by @AndyCrooks & colleagues
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#BigData #DataScience #AI #ComputationalScience #SocialScience -
Pandas Cookbook: Scientific Computing and Data Analysis with Python
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532-page #coding book by @TedPetrou >> "Pandas Cookbook: Recipes for Scientific Computing, #TimeSeries Analysis and Data Visualization using #Python" at http://
amzn.to/3KOQP1v
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#100DaysOfCode #DataScience #DataScientists #DataViz #MachineLearning #ComputationalScience -
Python Tools for Scientists: Anaconda, JupyterLab, Scientific Libraries Guide
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#Python Tools for Scientists: An Introduction to Using Anaconda, JupyterLab, and Python's Scientific Libraries => Get it at http://
amzn.to/3WrBmZf [700+ page book from @NoStarch Press]
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#Coding #BigData #DataScience #DataScientists #ComputationalScience #MachineLearning #AI -
Practical Data Quality Auditing Guide Using Python Ecosystem
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Practical #DataQuality Auditing — A Comprehensive Guide exploring how to leverage the #Python ecosystem: https://
towardsdatascience.com/data-quality-a
uditing-a-comprehensive-guide-66b7bfe2aa1a
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#BigData #DataStrategy #CDO #Analytics #DataScience #DataScientists #MachineLearning #Coding -
LangChain Introduces New Multi-Input Tool Agent
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However, we also introduced a new agent type that works with tools with multiple inputs This agent is ALSO compatible with older tools, so we would recommend using this by default Docs: https://
python.langchain.com/en/latest/modu
les/agents/agents/examples/structured_chat.html
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