To develop a recommendation system based on a user’s purchase history, you can use collaborative filtering, a technique commonly used for recommender systems. Collaborative filtering uses the past behavior of users and items to recommend items that other users with similar behavior liked in the past. Here are the steps…

GPT-2 GPT-2 (Generative Pre-trained Transformer 2) is a large-scale language model developed by OpenAI. GPT-2 is designed to generate human-like text by predicting the next word in a sequence of words, based on the words that came before it. …

1. What is the difference between bias and variance in machine learning?

What is standard deviation, and how is it used in statistics? Standard deviation is a measure of the variability or dispersion of a dataset. It tells us how much the individual data points deviate from the mean or average value of the dataset. …

The goal of the Competition The goal of this competition is to detect external contact experienced by players during an NFL football game. I will player tracking data to identify moments with contacts to help improve player safety. This is the imbalanced dataset. Nearly %8 of the data belongs to class 1. In order to…

A- NLP Basics NLP is a field of study based on making sense of texts and audios by using statistics and computations. This workbook includes: Topic identification Text Classification Chatbots Translation Sentiment Analysis 1- RegEx What regular expressions is for? It finds all web links in documents or texts Removes/replaces unwanted characters Match…

Mevsimsellik — yinelenen, ancak periyodik bir şekilde olmak zorunda olmayan — zaman serisi modellemesinin temelini oluşturur. Gerçek mevsimselliği yakalamak, model doğruluğunu büyük ölçüde artırmaktadır. Mevsimselliği algılama Mevsimsellik birçok şekilde mevcuttur: Tekli (ör. yıllık, perakendedeki aylık satışlar gibi) veya çoklu (ör. haftalık ve yıllık, Survivor oyları gibi). Periyodik (ör. Yeni Yıl’ın…

Using Time Zone In Practice

Dates are everywhere in Data Science & Analytics. Also, everywhere in the World of data; in voting, stock prices, sales, customer behaviors, etc. Knowing how to analyze data over time is a core skill for anyone who wants to be an expert in data related works. …