Computer vision is the field of study which deals with automating tasks that rely on visual inputs. Computer vision aims to give computers the ability to understand images and video as humans do. Today, computer vision is a popular research area that has found applications in various fields such as Continue Reading
“Machine Learning”
Machine Learning An Introduction to Neural Networks
Machine learning has quickly become one of the hottest fields in computer science. It is a promising technology that can help to automate and optimize many complex and time-consuming tasks. One of the most popular methods in the field of machine learning is neural networks. Neural networks are a type Continue Reading
How to Build a Sentiment Analysis App with OpenAI GPT-3 and Flask
Sentiment analysis is a powerful technique in natural language processing that helps determine the sentiment expressed in a piece of text. It involves analyzing the subjective information to classify the text into positive, negative, or neutral categories. In this tutorial, we will show you how to build a sentiment analysis Continue Reading
How to Use OpenAI Gym for Deep Q-Learning
OpenAI Gym is a popular Python library that provides a collection of environments to develop and compare reinforcement learning algorithms. One of the most well-known reinforcement learning algorithms is Deep Q-Learning (DQN), which combines the use of a deep neural network with the Q-learning algorithm to learn optimal policies. In Continue Reading
How to use LLMs for text summarization and abstraction
In recent years, there has been a tremendous improvement in the field of natural language processing (NLP) with the introduction of large language models (LLMs) like GPT-3, BERT, and T5. These models have revolutionized various NLP tasks, including text summarization and abstraction. Text summarization is the process of condensing a Continue Reading
How to use LLMs for text extraction and annotation
How to Use Language Model Libraries (LLMs) for Text Extraction and Annotation Language Model Libraries (LLMs) are powerful tools for text extraction and annotation. They leverage pre-trained language models to perform a wide range of natural language processing tasks, such as named entity recognition, part-of-speech tagging, and dependency parsing. In Continue Reading
How to Use TensorFlow.js for Image Classification
Image classification is a common task in machine learning where we train a model to classify images into different categories or labels. TensorFlow.js is a powerful library that allows us to run machine learning models directly in the browser using JavaScript. In this tutorial, we will learn how to use Continue Reading
How to use LLMs for video analysis and generation
Introduction Language-Conditioned Latent Models (LLMs) are a powerful technique that combines text-based language models with latent variable models to generate and analyze videos. LLMs allow us to provide textual prompts and generate video content that aligns with the given prompts. In this tutorial, we will explore how to use LLMs Continue Reading
How to Use OpenAI DALL-E for Text-to-Image Synthesis
OpenAI DALL-E is an amazing model that can generate high-quality images from textual descriptions. It uses a combination of deep learning and unsupervised learning techniques to learn the relationship between text and images. In this tutorial, we will walk you through the steps of using OpenAI DALL-E for text-to-image synthesis. Continue Reading
Working with Spark for big data analytics
Apache Spark is an open-source unified analytics engine for large-scale data processing. It is designed to be fast and general-purpose, making it ideal for big data processing tasks such as data preparation, machine learning, and graph processing. In this tutorial, we will cover the basics of working with Spark for Continue Reading