Would love to try this. Its a long enough context length that we can throw in the entire PyTorch codebase and ask questions.
Happy to document my experience and give feedback.
RESEARCH
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Testing Long Context AI Model with PyTorch Codebase Analysis
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Gemini 1.5 Pro Arrives with 1M Token Context Window
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Gemini 1.5 has arrived. Pro 1.5 with 1M tokens available as an experimental feature via AI Studio and Vertex AI in private preview. Then there’s this: In our research, we tested Gemini 1.5 on up to 2M tokens for audio, 2.8M tokens for video, and 10M tokens for text. From
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Google Introduces Gemini 1.5 Next Generation AI Model
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In December we began the Gemini Era, and we’ve continued to make relentless progress since. Today we’re thrilled to introduce the next generation: Gemini 1.5 – hugely enhanced performance, highly efficient architecture & long-context length breakthrough https://
blog.google/technology/ai/
google-gemini-next-generation-model-february-2024
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Independent Replication of Important Science Magazine AI Report
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Independent replication of a recent and important @ScienceMagazine report
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Python ML MLOps CV NLP LLMs Daily Tutorials
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If you are interested in: – Python – Machine Learning – MLOps – CV/NLP – LLMs Find me → @Sumanth_077 Everyday, I share tutorials on above topics! Like/RT the first tweet to help this reach more people!
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Implementing _predict_single Method for KNN Classification
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Finally a '_predict_single' method as mentioned it predicts the class label for a single data point This is done by: 1. Calculating the distance between one point to all training examples 2. Selecting the k-nearest Neighbours, & returning the most common class label among them
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Implementing fit Method and Euclidean Distance in KNN
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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 from Scratch Python
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K Nearest Neighbors (KNN) implemented from scratch in Python Here is the step by step explanation with code. Thread
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Essential Resources for Data Science ML and AI Learning
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End of this thread! If you are looking to learn more about
Data Science
ML/DL/AI
Analytics
Math & Statistics
Resources
LLMs
MLOps Then, Don't forget to follow me at @avikumart_ for upcoming posts -
Explore Data Science and Latest AI Applications on Futuresmart
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Check out many blogs on wide range of data science topics to latest SOTA AI applications only on Futuresmart AI blog