AI/ML Internship

An Introduction to AutoML: Basics, Benefits, and Getting Started

Automated Machine Learning, or AutoML, is a technology that simplifies the process of building machine learning models by automating various steps, from data preprocessing to model selection and tuning.

Guide to Transfer Learning with PyTorch

Using custom images with a pre-trained model like ResNet-18 is common in transfer learning to adapt the model to a specific task or dataset.

Transfer Learning: Accelerating Machine Learning with Pre-trained Models

Transfer learning offers a powerful solution by allowing us to leverage knowledge from a model trained on a similar task and apply it to a new, but related, problem.

Building and Training a Simple GAN Using PyTorch

Generative Adversarial Networks (GANs) are a type of deep learning model consisting of two neural networks—a generator and a discriminator—that compete against each other to produce high-quality, realistic data.

Building a DQN AI Agent with Python, PyTorch, and Pygame

This article will guide you through building a DQN AI agent that learns to navigate a simple 5x5 grid, avoiding obstacles and reaching a goal.

Reinforcement Learning with Gym: A Beginner’s Guide to CartPole

In this article, we will walk through the process of setting up and interacting with the CartPole environment using OpenAI’s Gym library.

Reinforcement Learning Introduction

Let's dive into the key concepts, explore algorithms, and get a feel of how agents learn through interaction and feedback.

An Introduction to Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) Networks: Modeling Sequential Data

Recurrent Neural Networks (RNNs) are a type of artificial neural network designed to handle sequential data by maintaining a form of memory. They excel in tasks where context over time is critical, such as speech recognition and natural language processing.

Predicting Movie Review Sentiment with Machine Learning

In this article, we will walk through the development of a sentiment analysis system using Python, focusing on movie reviews as the core data source.

Introduction to CNNs: Convolutional Layers, Pooling Layers, and Fully Connected Layers

Convolutional Neural Networks (CNNs) are a class of deep learning algorithms primarily used for processing structured grid data such as images.