Machine Learning Techniques

Data Sets Explainable AI Featured Posts Generative AI Natural Language Processing

Genome: Synthesizing DNA Sequences with LLM Techniques

This methodology is not focused on genome data alone. The purpose is to design a generic solution that may also work in other contexts, such as synthesizing molecules. The problem involves dealing with a large amount of “text”. Indeed, the sequences discussed here consist of letter arrangements, from an alphabet that has 5 symbols: A, […]

Courses Data Sets Generative AI Python

10 GenAI Notebooks: OpenAI, LLM, RAG, GPT, and More

For developers and AI/ML professionals. This comprehensive free resource offered by our sponsor is designed to provide you with hands-on experience and deeper insights into building cutting-edge GenAI applications. 🌟 Special Opportunity: You can win a pair of Apple Airpods simply by following the tutorial and learning something new. How to Participate Follow these 2 […]

Books Explainable AI Featured Posts Generative AI Machine Learning Statistical Science Synthetic Data Visualization

Easy Trick to Debias GenAI Models: Quantile Convolution

All of the GenAI apps that I tested, including my own, have the same problem. They cannot easily generate data outside the observation range. As an example, let’s focus on the insurance dataset discussed in my new book. I use it to generate synthetic data with GAN (generative adversarial networks) and the NoGAN models discussed […]

Books Deep Learning Featured Posts Generative AI Machine Learning Python

New Book: Understanding Deep Learning

By Simon Prince, computer science Professor at the University of Alberta. To be published by MIT Press, Dec 2023. The author shares the associated Jupyter notebooks on his website, here. Very popular, it got over 5,000 likes when the author announced the upcoming book on LinkedIn. I pre-ordered my copy. Summary An authoritative, accessible, and […]

Explainable AI Featured Posts Generative AI Podcasts Synthetic Data

NoGAN: Ultrafast Data Synthesizer – My Talk at ODSC San Francisco

My talk at the ODSC Conference, San Francisco, October 2023. Includes Notebook demonstration, using our open-source Python libraries. View or download the PowerPoint presentation, here. I discuss NoGAN, an alternative to standard tabular data synthetization. It runs 1000x faster than GAN, consistently delivering better results according to the most sophisticated evaluation metric, implemented here for […]

Experimental Math Featured Posts Machine Learning Python Statistical Science

Quantum Derivatives, GenAI, and the Riemann Hypothesis

Have you ever encountered a function or cumulative probability distribution (CDF) that is nowhere differentiable, yet continuous everywhere? Some are featured in this article. For a CDF, it means that it does not have a probability density function (PDF), and for a standard function, it has no derivative. At least, not until now. The quantum […]

Data Sets Experimental Math Featured Posts Python Statistical Science

Number Theory: Longest Runs of Zeros in Binary Digits of Square Root of 2

Studying the longest head runs in coin tossing has a very long history, starting in gaming and probability theory. Today, it has applications in cryptography and insurance. For random sequences or Bernoulli trials, the associated statistical properties and distributions have been studied in detail, even when the proportions of zero and one are different. Yet, […]

Books Explainable AI Featured Posts Generative AI Synthetic Data

New 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). This book covers optimization techniques pertaining to machine learning and generative AI, with an emphasis on producing better synthetic data with faster methods, some not even involving neural networks. NoGAN for tabular data is […]

Explainable AI Featured Posts Generative AI Machine Learning Podcasts Synthetic Data

NoGAN: New Generation of Synthetic Data (Video)

My talk at the Generative AI Conference, London, September 2023. View or download the PowerPoint presentation, here. I introduce a new, NoGAN alternative to standard tabular data synthetization. It is designed to run faster by several orders of magnitude, compared to training generative adversarial networks (GAN). In addition, the quality of the generated data is […]

Explainable AI Featured Posts Generative AI Python Statistical Science Synthetic Data

GenAI: Fast Data Synthetization with Distribution-free Hierarchical Bayesian Models

Deep learning models such as generative adversarial networks (GAN) require a lot of computing power, and are thus expensive. Also, they may not convergence. What if you could produce better data synthetizations, in a fraction of the time, with explainable AI and substantial cost savings? This is what Hierarchical Deep Resampling was designed for. It […]

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