Premium Post Machine Learning Multiple Linear Regression: Explained, Coded & Special Cases We explore the math and code for multiple linear regression, along with the two special cases: simple linear regression and polynomial regression.
Premium Post Linear Algebra Inverting A Matrix: Gaussian Elimination & Row Echelon Form Machine Learning algorithms make use of matrix inverses, but understanding how to invert a matrix is not easy. We walk through the theory and show you how to invert a matrix by example.
Premium Post Deep Learning Using Deep Learning To Take On COVID-19 Attempting and experimenting with identifying COVID-19 from X-Ray images, by using VGG19 with augmentation practices.
Premium Post Deep Learning Neural Network From Scratch with NumPy and MNIST Learn the fundamentals of how you can build neural networks without the help of the deep learning frameworks, and instead by using NumPy.
Premium Post Machine Learning Introduction To Machine Learning Deployment Using Docker and Kubernetes Walkthrough of deploying a Random Forest Model on a Toy Dataset. A Dockerfile, along with Deployment and Service YAML files are provided and explained.
Premium Post Machine Learning Stack Machine Learning Models - Get Better Results Model stacking will improve your results; but first, discover how it works and learn how to apply model stacking in Python.
Premium Post Machine Learning Web Scraping For Machine Learning - With SQL Database Machine Learning requires data. But what about when the data you need is not available as a dataset? What then? Do you pay someone, or do it yourself?
Premium Post Deep Learning TensorFlow 2.0 Tutorial in 10 Minutes TensorFlow is inevitably the package to use for Deep Learning, if you want the easiest deployment possible. On top of that, Keras is the standard API and is easy to use, which makes TensorFlow powerful for you and everyone else using it.
Premium Post Deep Learning Optimizers Explained - Adam, Momentum and Stochastic Gradient Descent Picking the right optimizer with the right parameters, can help you squeeze the last bit of accuracy out of your neural network model.
Premium Post Machine Learning How to use Grid Search CV in sklearn, Keras, XGBoost, LightGBM in Python GridSearchCV is a brute force on finding the best hyperparameters for a specific dataset and model. Why not automate it to the extend we can?
Premium Post Deep Learning Activation Functions Explained - GELU, SELU, ELU, ReLU and more Better optimized neural network; choose the right activation function, and your neural network can perform vastly better. 6 activation functions explained.
Premium Post Deep Learning Neural Networks: Feedforward and Backpropagation Explained & Optimization What is neural networks? Developers should understand backpropagation, to figure out why their code sometimes does not work. Visual and down to earth explanation of the math of backpropagation.
Premium Post Machine Learning Nested Cross-Validation Python Code Code for nested cross-validation in machine learning - unbiased estimation of true error. What is nested cross-validation, and the why and when to use it.
Premium Post Machine Learning Random Forest Explained Perhaps one of the most common algorithms in Kaggle competitions, and machine learning in general, is the random forest algorithm. It performs well in almost all scenarios and is mostly
Premium Post Statistics How to do Linear Regression and Logistic Regression in Machine Learning? Wondering how Linear Regression or Logistic Regression works in Machine Learning? Python code and a walkthrough of both concepts are available here.
