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Fundamentals of Neuroscience, Part 1: The Electrical Properties of the Neuron
Organic Chemistry 1
Mountains 101
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Explore embeddings in LLMs, their role in AI-powered tools, and practical applications using LlamaIndex and Chroma db. Gain insights into representing data for advanced language processing.
Learn to query databases and CSV files using natural language with LangChain and OpenAI, converting English to SQL or pandas commands for efficient data retrieval and analysis.
Learn to build an AI-powered Q&A system using LangChain and OpenAI. Explore text embeddings, vector stores, and agent chaining to create a custom question-answering tool with your own data.
Build an image classifier for orangutans and komodo dragons using PyTorch's torchvision library and a pretrained ResNet model. Learn to leverage pre-trained models for quick and effective computer vision tasks.
Explore Python's @cache and lru_cache decorators to optimize performance, reduce computations, and save resources with practical examples and comparisons.
Optimize Python code by replacing for-loops with vectorization techniques, improving efficiency and speed while maintaining readability and functionality.
Learn to build neural networks, understand PyTorch's computational graph, and visualize deep learning networks using PyTorchViz in this comprehensive tutorial.
Learn to automate developer workflows using Python's subprocess module. Build a CLI tool to create directories, initialize Git, set up virtual environments, and manage tasks efficiently.
Explore steganography and the Least Significant Bit algorithm for hiding messages in digital images, with Python code examples for embedding and extracting secret data.
Learn to create professional CVs using R and RStudio with the vitae package. Explore 6 templates and leverage markdown for customization in this efficient, programmer-friendly approach to resume building.
Learn Python unit testing techniques, mock print outputs, and update PyPI packages to enhance your development skills and package management abilities.
Learn to implement weekly rolling sums using Python's standard library, exploring itertools' groupby, enumerate, and isocalendar. Enhance your data manipulation skills without relying on external libraries like pandas.
Explore techniques for refactoring monolithic Python functions into smaller, modular, and testable units. Learn mental models for writing maintainable and predictable code.
Deploy smart contracts to Rinkeby testnet, set up brownie-config, and validate on Etherscan. Learn to use test ETH from faucets and enable web3 wallet transactions with your contract.
Learn to create, structure, and publish a Python package on PyPI, covering setup.py, distribution types, and the upload process in under 15 minutes.
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