Detail Explanation of Code For Beginners I wrote a tutorial on some common transform functions in Apache Beam in a previous tutorial that covered map, filter, and combinePerKey(). This tutorial will be for ParDo transform which is nothing but another way of doing Map. But the difference is ParDo applies…

Use of Hyperband Tuner with Complete Code — TensorFlow can be highly efficient, but the process of finding the right parameters can be very tiring and tedious. On the other hand, it won’t be as great without the right parameters. All of my previous tutorials on Tensorflow showed very good results. But I only presented my last version…

Let’s Practice with Some Real Data — Apache Beam is getting popularity as the unified programming model for efficient and portable big data processing pipelines. It can deal with both batch and streaming data. That’s how the name comes from. Beam is combination of the words Batch and Stream: B(from Batch) + eam(from stream)= Beam The portability…

Complete code in Python — I have been writing tutorials on Machine learning, deep learning, data visualization, analysis, and statistics for some time. But I realized I didn’t write too much about some simple machine learning pipelines that can be very useful. …

A deep Convolutional Neural Network for more efficient Image Recognition — VGG Network is the basis for one of the most popular image recognition techniques. It is worth learning because it opens a lot of avenues. You need to understand how a Convolutional Neural Network (CNN) to understand VGGNet. …

Using Canny Edge Detection Efficiently — Edge detection is very common and widely used image processing necessary for many different computer vision applications like data extraction, image segmentation, and in more granular level feature extraction, and pattern recognition. …

Simple, Otsu, and Adaptive Thresholding Implementation with Examples — One of the most commonly used segmentation techniques is thresholding. It is widely used in computer vision and is very useful to separate the object that we are interested in from the background. This article will focus on the thresholding techniques in OpenCV. There are three different types of thresholding…

Erosion, dilation, opening, closing, morphological gradient, tophat / whitehat, and blackhat explained with examples — In my last article, I wrote about some basic image processing in OpenCV. Today, we will advance a little bit and work on the morphological operations which are commonly used in image processing. Morphological operations are used to extract the region, edges, shapes, etc. What are Morphological Operations?

OpenCV for beginners: move or translate, resize, and cropping — One of the most used libraries for handling image processing and manipulation is openCV for Python users. For image classification, object detection, or optical character recognition, any work related to images in the AI world need some kind of image processing and manipulation most of the time. …