Deep Learning - Nomidl

Fine-Tuning BERT for 90%+ Accuracy in Text Classification

What are Pretrained Language Models? Pretrained Language Models (PLMs) are deep learning models trained on large corpus of text to understand the structure and nuances of natural language. These models are used as a foundation for various Natural Language Processing (NLP) tasks, including Fine tuning BERT for text classification, significantly improving performance compared to training from…

Markov Decision Process (MDP): The Foundation of RL

Machine learning employs reinforcement learning (RL) as a strong paradigm which allows agents to optimize their decisions through environmental experience. The mathematical core of decision-making problems in RL exists within the Markov Decision Process (MDP) framework. MDPs establish the fundamental framework in reinforcement learning which makes them essential knowledge for anyone working with this field.…

A Comprehensive Guide on Attention-Based RAG

The advanced model Attention-Based RAG (Retrieval-Augmented Generation) extends RAG principles through attention mechanisms to improve both retrieval precision and document synthesis. This method utilizes self-attention techniques together with cross-attention approaches to improve document selection and content synthesis thus generating more contextually appropriate responses. Extensive research is presented in this article through a deep analysis of…

Understanding the Perceptron Neural Network

What is a Perceptron? A perceptron is a simple type of neuron in a neural network. Here’s what a perceptron does: it takes in several inputs (denoted as x1, x2, …, xn) and produces a binary output, essentially making a decision. The perceptron multiplies these inputs by corresponding weights (w1, w2, …, wn), computes the…

How to Become a Prompt Engineer in 2024

In this article, we will explore the role of prompt engineers in the field of AI technology. Prompt engineers play a crucial role in enabling AI models to generate relevant output based on user input. We will discuss the basics of prompt engineering, its importance, and the steps and skills required to become a proficient…

How to Create an Image Classification Model using Hugging Face in 5 Lines

In 2021, when it comes to natural language processing tasks, most people turn to Hugging Face for solutions. However, did you know that Hugging Face now also offers image-related solutions? Yes, you heard it right! The popular Transformers library can now help you classify images as well. In this blog post, I will show you…

Building a Classification Model with VGG19 for Image Recognition

Image classification is a fascinating field of machine learning that involves teaching a computer to recognize and categorize objects or patterns within images. In this article, we will walk through the process of building a classification model using the VGG19 architecture for image recognition. We’ll start from importing the necessary libraries and proceed step by…

Generating new MNIST digits in PyTorch using AutoEncoder

Are you curious about how machines can learn to understand and generate images? In this blog post, we’re going to delve into the fascinating world of Autoencoders using PyTorch, and we’ll explain this concept in simple terms. Autoencoders are a type of artificial neural network that can compress data and then reconstruct it. This article…

Top 10 Best AI Companies in 2024

In our fast-changing world, new ideas are really important for making progress. One big idea that’s changing things a lot is called artificial intelligence, or AI for short. AI isn’t just something for the future; it’s already making big changes in the world, and it’s doing it with a level of accuracy that used to…

Denoising Images with Autoencoders Using TensorFlow and Python

In today’s digital world, images play an important role in various applications, from medical imaging to self-driving cars. However, images are often corrupted by noise during transmission or storage, which can hinder the performance of image processing algorithms. In this blog post, we will explore how to use autoencoders to denoise images. We will implement…