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1. How to Generate Instruction Datasets from Any Documents for LLM Fine-Tuning

   Generate instruction datasets for fine-tuning Large Language Models (LLMs) using lightweight libraries and documents.

   2024-04-04 Tags: llm, fine-tuning, instruction datasets, towardsdatascience by klotz
2. Demystifying Matplotlib

   There’s a reason you’re confused

   2023-11-03 Tags: matplotlib, machine learning, statistics, pandas, python, model, towardsdatascience by klotz
3. Crafting Effective Prompts for Summarization Using Large Language Models

   Distilling key points after >2 years of experience and from AI developers’ own tutorials, hands-on and with examples.

   2023-11-03 Tags: llm, prompt engineering, summarization, towardsdatascience by klotz
4. Using Large Language Models as Recommendation Systems

   A review of recent research and a custom implementatuon

   2023-10-25 Tags: mohamad aboufoul, towardsdatascience, llm, collaborative filtering, recommender, survey by klotz
5. An Introduction to OpenAI Function Calling | by David Hundley | Jul, 2023 | Towards Data Science

   2023-07-25 Tags: openai, function, david hundley, towardsdatascience, llm by klotz
6. DBSCAN Clustering: Break It Down For Me | by Shreya Rao | Nov, 2022 | Towards Data Science

   2022-12-22 Tags: machine learning, dbscan, medium, towardsdatascience, clustering, algorithms by klotz
7. The Causal Inference “do” Operator Fully Explained, with an End-to-End, Example Using Python and DoWhy | by Graham Harrison | Dec, 2022 | Towards Data Science

   2022-12-20 Tags: causal, inference, do operator, python, root cause analysis, towardsdatascience by klotz
8. Beginner’s Guide to the GPT-3 Model | by Jin Cui | Towards Data Science

   2022-06-08 Tags: gpt-3, machine learning, nlp, text, api, towardsdatascience by klotz
9. SBERT vs. Data2vec on Text Classification | by Jinhang Jiang | May, 2022 | Towards Data Science

   Each time you run the model, the results may vary a little bit. Overall, after 5 tries, I can conclude that SBERT has a bit better performance in terms of best f1 score while Data2vec used way less memory. The average f1 scores for both models are very close.

   2022-05-19 Tags: sbert, data2vec, text, classification, multi-label, nlp, machine learning, towardsdatascience by klotz
10. Enrich your Jupyter Notebook with these tips | by Zolzaya Luvsandorj | Nov, 2021 | Towards Data Science

    $$logloss(theta) = - {1 over m} sum_{i=1}^m (y_i ln(hat p(y_i=1)) + (1-y_i) ln(1-hat p(y_i=1)))$$

    2021-12-01 Tags: jupyter, markdown, latex, visualization, math, formatting, machine learning, data science, documentation, towardsdatascience, medium by klotz

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