Deep learning is a subset of machine learning that involves training artificial neural networks to learn and recognize patterns in large datasets. These neural networks are composed of many layers of interconnected nodes, which are trained to recognize and extract features from input data. Deep learning requires powerful hardware for a few reasons: Overall, deep […]
Category: deep learning
Object Detection using YOLOv5: A Simple Guide
YOLOv5 is one of the popular object detection algorithm YOLO (You Only Look Once) which was released in June 2020 and was developed by Glenn Jocher and the team at Ultralytics. YOLOv5 is a single-stage object detection algorithm, which means that it performs object detection in a single pass through the network, as opposed to […]
Deep Learning Models with TensorFlow and Keras: A Guide to Sequential, Functional, CNN, RNN and Autoencoder Models with Example Code
TensorFlow is a powerful and popular deep learning library, and Keras is a high-level API built on top of TensorFlow that makes it easier to build and train deep learning models. Here are some common types of deep learning models that you can build using the tf.keras API: These are just a few of the […]
A Simple Guide to Convolutional Neural Networks
Convolutional Neural Networks (CNNs) have revolutionized the field of deep learning in recent years. They are a type of neural network that is especially effective for image recognition tasks, but can also be applied to other types of data, such as audio and text. In this article, we will provide a simple guide to CNNs, […]
Building a Deep Learning Model: A Step-by-Step Guide
Deep learning is a subset of machine learning that uses neural networks to perform complex tasks such as image recognition, natural language processing, and speech recognition. In this tutorial, we will walk through the steps to build a deep learning model using Python and Keras. Step 1: Set up the Environment Before we begin building […]
Data Augmentation: Techniques and Best Practices for Machine Learning and Computer Vision
Data Augmentation is a technique used in machine learning and computer vision to artificially increase the size of a dataset by creating new, slightly modified versions of existing data. It is typically done by applying various transformations such as rotation, cropping, scaling, flipping, adding noise, and more, to the original data. The resulting augmented data […]
Deep Learning FAQs
Introduction Deep Learning is a subset of Artificial Intelligence that uses algorithms to learn from data and make decisions. It is used in many areas, such as computer vision, natural language processing, and robotics. What is the difference between Deep Learning and Machine Learning? Deep learning and machine learning are two of the most popular […]
Google Colab GPU for Beginner
Google Colab GPU is a free cloud service offered by Google that allows users to run their code on a remote GPU. This service is available to all users, and no setup is required. It is primarily used for interactive use cases and provides users with access to more reliable resources than other free cloud […]
Deep Learning and Image Classification: Tips for Beginners
Deep learning has revolutionized the field of computer vision, making it possible to solve complex image classification problems with high accuracy. If you’re a beginner looking to get started with deep learning and building image classifiers, here are some tips to help you get started. As a beginner, it’s important to start with a simple […]
Becoming a TensorFlow Developer: Essential Skills and Resources
TensorFlow is one of the most popular open-source software libraries for machine learning and deep learning. As a result, the demand for TensorFlow developers is on the rise, and many professionals are looking to add this skill to their toolkit. In this article, we’ll discuss the technical skills that are necessary to be a TensorFlow […]
