Training AI on Amazon Electronic Reviews Using #Python for Natural Language! – by – @gp_pulipaka
! JupyterLab/Jupyter Notebook WordNet, Lexical Semantic Relation Analyzer
Thesaurus, 155,000 Words
Synset 115,000, 205,000 word-Sense Pair. NLTK Library, spaCy, TextBlob
AI
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Training AI Models on Amazon Electronic Reviews using Python and NLTK
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Machine Learning Educational Course and Event Announcement
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1974 Machine Learning! @bigdataconf A Greater Foundation for Machine Learning. Welcome to Python, TensorFlow, and PyTorch. Register and join me in the new year. Join and learn at your own pace. Machine Learning for all the ages. @bigdataconf #BigData #Analytics #DataScience
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The Tradeoff Between Traditional Coding and AI-Generated Code
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Stack Overflow gave you an answer you could read and understand. AI gives you code you can run without understanding it. Different tradeoff.
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Limitations of LLM-based content filtering
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A filter that works only when the model reads the title is not really a filter.
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OpenAI’s Strategy for Mainstream AI Adoption
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Natural conversation and useful memory are the two things that make people recommend a product to someone who doesn't care about AI. That's the market OpenAI is going after here.
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Using Thread Automations for Persistent AI Agent Context
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thread automations are slept on they let Codex wake up inside the same thread on a schedule so instead of restarting context every time, it can keep checking, reviewing, polling, or continuing exactly where it left off tiny feature. very useful.
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Using Encoder-Decoder LSTMs for Machine Translation
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Using Encoder Decoder LSTMs to Perform Translation. #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #CloudComputing #Serverless #Linux #Programming #Coding #100DaysofCode https://
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Comparing AI coding model performance in practical tasks
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Two days of failure on a $200 plan followed by a one-shot Codex solution on a $100 plan is a brutal side by side.
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Discussion on AI Model Autonomy and Reliability Issues
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The autonomy issues with 4.7 probably have something to do with this. Hard to trust a model that goes off script.
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Impact of hallucination reduction on AI use case viability
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Hallucinaton reduction at that scale would change which use cases are actually viable, not just which ones work most of the time.