If you want to become an expert in machine learning, you must also learn deep learning. There are many paid and free courses on the internet that can give you a comprehensive knowledge of the concepts of deep learning. So,…
Deep learning is a subset of machine learning in which we use the power of neural network architectures that mimic the workings of a human brain while solving a problem. If you want to become a machine learning engineer, you have…
Both PyTorch and TensorFlow have been used in industry for a long time. These two frameworks are the best in the features they provide for deep learning. So what should you learn? In this article, I’ll walk you through what…
The use of deep neural architectures instead of the classic machine learning algorithms to train bigger models that can mimic the human brain while solving complex problems that involve heavy computing is known as deep learning. In this article, I…
When we use deep neural architecture instead of classic machine learning algorithms, it’s nothing but deep learning. In this article, I’m going to introduce you to some of the best deep learning projects with Python that you should try as…
Many machine learning algorithms can be used to solve complex problems that require a large amount of data with a large number of features, but deep learning can outperform all algorithms. So to understand where we can use deep learning…
Humans have an inherent ability to transfer knowledge between tasks. What we acquire as knowledge while learning a task, we use it in the same way to solve related tasks. The more the tasks are linked, the easier it is…
Deep learning is a subset of Artificial Intelligence, which is an area that relies on learning and improving on its own by examining computer algorithms. While machine learning uses simpler concepts, these models work with artificial neural networks, designed to…
In this article, I will take you through a brief explanation of Image Segmentation in Deep Learning. I will only explain the concept behind the image segmentation here in this article. If you want to go through the practical part…
Being a practitioner in Machine Learning, you must have gone through an image classification, where the goal is to assign a label or a class to the input image. Now, suppose you want to get where the object is present…
Machine Learning Pipelines performs a complete workflow with an ordered sequence of the process involved in a Machine Learning task. In most of the functions in Machine Learning, the data that you work with is barely in a format for…
TensorBoard is a great interactive visualization tool that you can use to view the learning curves during training, compare learning curves between multiple runs, visualize the computation graphs, analyze training statistics, view images generated by your model, visualize complex multidimensional…
Most of the keyboards in smartphones give next word prediction features; google also uses next word prediction based on our browsing history. So a preloaded data is also stored in the keyboard function of our smartphones to predict the next…
Data Augmentation is a technique in Deep Learning which helps in adding value to our base dataset by adding the gathered information from various sources to improve the quality of data of an organisation. Data Augmentation is one of the…
Birds inspired us to fly, nature inspired us to countless inventions. It seems logical, then to look at the brain’s architecture for inspiration on how to build an Intelligent Machine. This is the logic that sparked Artificial Neural Networks (ANN).…
There are two main approaches to training models across multiple devices; model parallelism, where the model is split across the devices, and data parallelism, where the model is replicated across every device, and each replica is trained on a subset…
In this article, I will take you through a very powerful algorithm in Machine Learning, which is the Grid Search Algorithm. It is mostly used in hyperparameters tuning and models selection in Machine Learning. Here I will teach you how…
In this article, we will look at how to speed up your models by using a GPU. We will also see how to split the computations across multiple devices, including the CPU and numerous GPU devices. Thanks to GPUs, instead…
PyTorch is a library in Python which provides tools to build deep learning models. What python does for programming PyTorch does for deep learning. Python is a very flexible language for programming and just like python, the PyTorch library provides…
If you want to deploy your TensorFlow model to a mobile or embedded device, a large model may take too long to download and use too much RAM and CPU, all of which will make your app unresponsive, heat the…
According to the report of Centers of Disease Control and Prevention about one in seven adults in the United States have Diabetes. But by next few years this rate can move higher. With this in mind today, In this article,…
TensorFlow is a powerful library for numerical computation, particularly well suited and fine-tuned for large–scale Machine Learning ( but you could use it for anything else that requires heavy calculations). The Google Brain team developed it, and it powers many…