The exponential smoothing algorithms are popularly used for forecasting univariate time series. We will see how to use them in MS Excel.
Non-max suppression is used in various object detection algorithms like yolo, ssd. Understand how non-max suppression with implementation.
Learn the differences between the most commonly used boosting algorithms in ML - GBM, XGboost, LightBoost, and CatBoost, and how they work.
An introduction to neural networks. Understand the math behind convolutional neural networks with forward and backward propagation & Build a CNN using NumPy.
Pandas 1.0 is out! This comes with key changes that you should know about. Here are 4 features that will change the way you used Pandas before.
Feature engineering for time series data can give you an edge over your competition. Learn how to perform this technique for time series data using python.
Gaussian mixture model is a distribution based clustering algorithm. How gaussian mixture models work and how to implement in python.
Learn about SIFT(scale invariant feature transform), a powerful algorithm in computer vision. Understand what it is, sift computer vision.
Skimage tutorial to learn how it works and also 8 powerful skimage tricks to make you a computer vision expert. Get started with skimage Python here.
HOG descriptor is used in computer vision. Learn about feature descriptor and feature extraction for images using HOG feature descriptor.
