Next define the "fit" method that takes the training data(X) and it's corresponding labels(y) and stores them. This is the reason why the computation cost is high as it stores all the training data! And also a method to calculates the euclidean distance between two data points.
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K Nearest Neighbors KNN Implementation Python Step by Step
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K Nearest Neighbors (KNN) implemented from scratch in Python (step-by-step explanation with code):
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KNNClassifier Class Initialization: Choosing the Optimal k Value
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Define the KNNClassifier class and initialize the number of Neighbours (k) to be considered in __init__ method Defining the K value is critical in KNN! A small value of k means noise will have a higher influence on the result and a large value makes it computationally expensive
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Eight Generative AI Buzzwords Explained and Simplified
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8 Generative AI buzzwords explained! https://
datasciencedojo.com/blog/generativ
e-ai-use-cases-and-concepts/
… #AI #MachineLearning #DeepLearning #DataScience #GenerativeAI #ChatGPT #OpenAI #OpenScience #LLM #LLMs #Python #Code #100DaysOfCode @DataScienceDojo Source @jblefevre60 -
Scraping Dynamic Websites with Python: A Productivity Guide
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Python and Scraping are best friends. Learn how productive their friendship can be 😉 How to scrape dynamic websites with Python.
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llm.c optimization: balancing historical accuracy and training speed
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This is cool!! I'm not exactly sure how to upstream these changes to llm.c… Part of me wants to reproduce GPT-2/3 using their exact hyperparameters just for historical aesthetics, but part of me also wants to just train things as fast as possible. Probably both. – lr 3X is
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LLM Apps with RAG Demos in GitHub Repository
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Find all the awesome LLM Apps demo with RAG in the following Github Repo. P.S: Don't forget to star the repo to show your support
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Streamlit Gemini Multimodal Chatbot Application Demo
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Working Application demo using Streamlit
— Shubham Saboo (@Saboo_Shubham_) 7 juin 2024
Paste the above code in vscode or pycharm and run the following command: 'streamlit run gemini_multimodal_chatbot.py' pic.twitter.com/oUYSPsEHmCWorking Application demo using Streamlit Paste the above code in vscode or pycharm and run the following command: 'streamlit run gemini_multimodal_chatbot.py'
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Full Multimodal Chatbot with Google Gemini Flash
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Full Multimodal Chatbot code using Google's Gemini Flash
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Building Gemini Flash Chatbot with Image Upload and History
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7. Generate Response and Display • If a prompt is entered, add the user message to the chat history and display it
• If an image is uploaded, add it to the inputs list
• Generate a response using the Gemini Flash
• Display the assistant response in the chat message container