Author: admin
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Prompt Engineering
The Prompt Report: A Systematic Survey of Prompting Techniques https://arxiv.org/abs/2406.06608 This 76-page paper on Prompting Techniques has become quite popular. A nice read for your weekend. – “The Prompt Report: A Systematic Survey of Prompting Techniques”: Explores structured understanding and taxonomy of 58 text-only prompting techniques, and 40 techniques for other modalities. The paper…
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Problem: undefined reference to `boost::this_thread::disable_interruption::~disable_interruption()’Problem:
Problem: undefined reference to `boost::this_thread::disable_interruption::~disable_interruption()’ Solution: Add options to g++ / clang++ -lboost_thread -lboost_system Reference https://stackoverflow.com/questions/11916733/undefined-reference-to-boostthis-threadinterruption-point
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How to copy jupyter notebook table into MS applications
Howto: g Howto: https://datascience.stackexchange.com/questions/126762/way-to-copy-paste-notebook-output-table-into-ms-tools
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Some papers on efficiency of Rust programming language
Here are some papers that explore Rust’s energy efficiency: 1. “Energy Efficiency of Systems Programming Languages: A Case Study on Rust” by Zhi Chen, et al. (2020) This paper compares the energy efficiency of several programming languages, including C, C++, Java, and Rust. The authors use a custom-built benchmarking framework to evaluate the energy consumption…
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Complete Set of Results from Paper Energy Efficiency Across Programming Languages (2017)
Original paper: “Energy efficiency across programming languages: how do energy, time, and memory relate?“ Original link: https://sites.google.com/view/energy-efficiency-languages/results?authuser=0 A. Data Tables binary-trees fannkuch-redux fasta k-nucleotide mandelbrot n-body pidigits regex-redux reverse-complement spectral-norm B. Normalized Global Results D. Pareto Optimal Set
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Train 70B Language Model on 2 24GB GPUs
You can now train a 70b language model at home https://www.answer.ai/posts/2024-03-06-fsdp-qlora.html
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Clustering Algorithms
A list of clustering algorithms References
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Dive into Deep Learning
Aston Zhang, Zachary Lipton, Mu Li and Alex Smola, 2022 (http://alex.smola.org/projects.html) This book covers code, math, examples and explanations in one piece. Some of the highlights:
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100 Days of Machine Learning Challenge
A machine learning challenge repo with insightful infographics, tutorials, codes and more. Take this challenge and start diving into machine learning coding. https://github.com/Avik-Jain/100-Days-Of-ML-Code
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Machine Learning, Artificial Intelligence and Data (MAD) 2021
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