New Book: Building Disruptive AI & LLM Technology from Scratch https://lnkd.in/eT4wrhA4 This book features new advances in game-changing AI and LLM technologies built by GenAItechLab.com. Written in simple English, it is best suited for engineers, developers, data scientists, analysts, consultants and anyone with an analytic background interested in starting a career in AI. The emphasis is on scalable enterprise solutions, easy to implement, yet outperforming vendors both in term of speed and quality, by several orders of magnitude. Each topic comes with GitHub links, full Python code, datasets, illustrations, and real-life case studies, including from Fortune 100 company. Some of the material is presented as enterprise projects with solution, to help you build robust applications and boost your career. You don’t need expensive GPU and cloud bandwidth to implement them: a standard laptop works. Part 1: Hallucination-Free LLM with Real-Time Fine-Tuning Part 2: Outperforming Neural Nets and Classic AI Part 3: Innovations in Statistical AI About the author Vincent Granville is a pioneering GenAI scientist and machine learning expert, co-founder of Data Science Central (acquired by a publicly traded company in 2020), Chief AI Scientist at ML Techniques and GenAI Techlab, former VC-funded executive, author (Elsevier) and patent owner — one related to LLM. Vincent’s past corporate experience includes Visa, Wells Fargo, eBay, NBC, Microsoft, and CNET. ➡️ See content and get your copy, at https://lnkd.in/eT4wrhA4
GenAItechLab.com
Technology, Information and Internet
Better, faster, less expensive GenAI apps. Includes XLLM, a customized GPT-like app self-tuned based on user feedback.
About us
Better, faster, less expensive GenAI apps. Includes XLLM, a customized GPT-like app self-tuned based on user feedback, with separate taxonomies and embedding tables for each top category. Enter your query, along with a potential category to narrow down your search and get more relevant results.
- Website
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https://genaitechlab.com/
External link for GenAItechLab.com
- Industry
- Technology, Information and Internet
- Company size
- 2-10 employees
- Headquarters
- Seattle, WA
- Type
- Privately Held
- Founded
- 2023
- Specialties
- GenAI, Synthetic Data, and LLM
Locations
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Primary
Get directions
Seattle, WA, US
Employees at GenAItechLab.com
Updates
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Hurwitz-Riemann Zeta And Other Special Probability Distributions
Hurwitz-Riemann Zeta And Other Special Probability Distributions - DataScienceCentral.com
https://www.datasciencecentral.com
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New Book: Building Disruptive AI & LLM Technology from Scratch
Building Disruptive AI & LLM Technology from Scratch - Machine Learning Techniques
http://mltechniques.com
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The music of the Riemann Hypothesis: Sound Generation in Python
The music of the Riemann Hypothesis: Sound Generation in Python - DataScienceCentral.com
https://www.datasciencecentral.com
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Book: Understanding Deep Learning
New Book: Understanding Deep Learning - Machine Learning Techniques
http://mltechniques.com
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New Interpolation Methods for Data Synthetization and Prediction - Python code, application to temperature geospatial data and ocean tides dataset
New Interpolation Methods for Data Synthetization and Prediction - Machine Learning Techniques
http://mltechniques.com
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Defining and Measuring Chaos in Data Sets: Why and How, in Simple Words
Defining and Measuring Chaos in Data Sets: Why and How, in Simple Words - DataScienceCentral.com
https://www.datasciencecentral.com
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Book: Statistical Optimization for Generative AI and Machine Learning. With case studies, Python code, new open source libraries, and applications of the GenAI game-changer technology known as NoGAN (194 pages).
New Book: Statistical Optimization for Generative AI and Machine Learning - Machine Learning Techniques
http://mltechniques.com
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Will ChatGPT Make Fraud Easier?
Will ChatGPT Make Fraud Easier? - DataScienceCentral.com
https://www.datasciencecentral.com
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Advanced Machine Learning with Basic Excel: Part 1
Advanced Machine Learning with Basic Excel – Part 1 - Machine Learning Techniques
http://mltechniques.com