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…
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…
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…
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…
I have several tutorials on Tensorflow where built-in loss functions and layers had always been used. But Tensorflow is a lot more dynamic than that. It allows us to write…
Matplotlib is arguably the most popular visualization library in Python. The library is big and it is hard to really learn everything in the library. I have shared quite a…
Precision, recall, and f1-score are very popular metrics in the evaluation of a classification algorithm. It is very easy to calculate them using libraries or packages nowadays. But I believe…
Outliers can be a big problem in data analysis or machine learning. Only a few outliers can totally alter a machine learning algorithm's performance or totally ruin a visualization. So,…
Null values are a big problem in machine learning and deep learning. If you are using sklearn, TensorFlow, or any other machine learning or deep learning packages, it is required…
In most of the DataFrames, we see one index that works as a row identifier. But what if there is more than one index in a DataFrame. Is multi-index DataFrames…