So lets first understand what is object detection? Object Detection models are one of the most widely used models among other computer vision tasks. Object detection is a task where we want our model to distinguish the foreground objects from the background and predict the locations and the categories for the objects present in the […]
Transformers have been the de-facto for NLP tasks, various pretrained models are available for translation, text generation, summarization and more. The models can be downloaded and fine tuned in your deep learning framework of choice as it plays nicely with Tensorflow, Pytorch and Jax. Transformers aren’t just for text any more- they can handle a […]
Spatial Transformer The spatial transformer module consists of layers of neural networks that can spatially transform an image. These spatial transformations include cropping, scaling, rotations, and translations etc CNNs perform poorly when the input data contains so much variation. One of the solutions to this is the max-pooling layer. But then again, max-pooling layers do […]
Recently, while exploring computer vision got a chance to train YoloV3 on custom dataset for object detection. We custom trained the YOLO V3 to detect following classes:– hardhat– vest– mask– boots Below is a short video demonstrating how amazingly the model is able to detect these objects. Code for this can be found here.
Transformers are getting more and more important not just in NLP but now its going to extend its surface area into other areas of deep learning beyond just language. Google has rolled out BERT and transformer based models to google search, they have been using them to empower google search and they call it one […]
Traditionally, Recurrent neural networks (RNNs) with LSTM or GRU units are the most prevalent tools for NLP researchers, and provide state-of-the-art results on many different NLP tasks, including language modeling (LM), neural machine translation (NMT), sentiment analysis, and so on. However, a major drawback of RNNs is that since each word in the input sequence […]
We humans have an amazing ability to rapidly interpret and put words into context while we exchange our thoughts and interact with others and the credit goes to the best computer we have ever know : A Human Brain. Over the years Scientists have carried out various research and have found that it involves a huge […]
PyTorch — Getting Started The purpose of this blog post is to outline the steps to create a new PyTorch virtual environment Firstly, Download and install Anaconda (choose the latest Python version). Login to Anaconda prompt and create a .yml file (pytorch_env.yml) with below configuration name: pytorch_gpu channels: — defaults — pytorch dependencies: — numpy=1.16.2 — pandas=0.24.2 — matplotlib=3.0.3 […]
When we talk about Machine Learning and Deep Learning, terms that we frequently come across is linear and non linear functions. Although, we would have studied this in our high school math, there will be at least a handful of them like me who would like to brush up on these mathematical terminologies. This blog […]
Line can be used to represent all sorts of information, in math we often use line to show the rate at which the amount is changing. Lets go ahead and explore the idea: Suppose, you would like to invest in something where your could get better returns and below are 4 lines (say investment types) […]
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