Category Archives: Machine Learning

Briefly: The term warm-start training applies to standard neural networks, and the term fine-tuning training applies to Transformer architecture networks. Both are essentially the same technique but warm-start is ineffective and fine-tuning is effective. The reason for this apparent contradiction … Continue reading →

ChatGPT is a chatbot that is based on the GPT-3 neural transformer model. ChatGPT was trained on an enormous corpus of English text — all of Wikipedia, books, Web sites, and so on. In ways that aren’t fully understood, ChatGPT … Continue reading →

It had been a while since I exercised my C# language skills, so I decided to refactor a Python example of logisitic regression. The goal is to predict the sex of a person (male = 0, female = 1) from … Continue reading →

A few days ago I implemented solution to the Traveling Salesman Problem (TSP) using an evolutionary algorithm, implemented in the C# language. As I was writing the C# code, I suspected that the same problem implemented using Python would have … Continue reading →

I was looking at spectral clustering with the scikit-learn library. Standard k-means clustering doesn’t work well for data that has weird geometry. A standard example is data that when graphed looks like two concentric circles. Spectral clustering connects data into … Continue reading →

I contributed to an article titled “Researchers Evaluate the Top Four AI Stories of 2022” in the January 2023 edition of the Pure AI web site. See https://pureai.com/articles/2023/01/05/top-ai-stories-of-2022.aspx. I am a regular contributing editor for the Pure AI site. For … Continue reading →

I did an Internet search for “What are correct values for precision and recall when the denominators equal 0?” and was pointed to a StackExchange page which had been up for over 11 years — and which was somewhat ambiguous. … Continue reading →

I wrote an article titled “Logistic Regression from Scratch Using Raw Python” in the January 2023 edition of Microsoft Visual Studio Magazine. See https://visualstudiomagazine.com/articles/2023/01/18/logistic-regression.aspx. Logistic regression is a machine learning technique for binary classification. For example, you might want to … Continue reading →

An epsilon-greedy algorithm is a general approach that can be used for many different problems. I recently devised a nice evolutionary algorithm for the Traveling Salesman Problem (TSP) that seems to work very well. Just for fun, I spent one … Continue reading →

GPT-3 (“Generative Pre-trained Transformer”) is a large language model that can generate text, such as a response to, “Write two paragraphs about the history of computer programming.” GPT3 was trained on an enormous corpus of text — Wikipedia, books, blogs, … Continue reading →