Machine Learning 101: Key Terminologies Explained
Discover key machine learning terminologies: algorithms, datasets, neural networks, and more in this easy-to-understand guide to AI basics.
Tag: supervised learning
Understanding Basic Machine Learning Concepts
Explore basic machine learning concepts in this guide. Learn about types of machine learning, key terms, and real-world applications.
Data Visualization & Training Regression Model Using LazyPredict
Learn how to visualize data and find an optimal regression model using lazypredict package with alltime top 500 movies dataset.
Example of Classifying 3D Figures With Tensorflow
Learn from this simple example about how to make a machine learning model for classifying 3D figures, in this case, from 3D MNIST dataset.
How To Make a Speech Recognition Algorithm
Learn how to make a simple speech recognition algorithm using Google's machine learning library Tensorflow.
Activation Functions in Artificial Neural Networks
Explore activation functions in neural networks, their types, and how to choose the right one for optimal deep learning performance.
Random Forest Regression With Python
Explore random forest regression, including fundamentals, advantages, limitations, applications, and performance improvement techniques.
Artificial Neural Networks for Regression With Python
Discover artificial neural networks for regression, network architecture, optimization, and performance-enhancing techniques.
Stochastic Gradient Descent With Python
Explore stochastic gradient descent, its advantages, limitations, applications, and hyperparameter tuning.
Polynomial Regression With Python Example
Explore polynomial regression with this guide, covering its foundations, advantages, limitations, and practical applications.
Elastic Net in Linear Regression With Python
Explore elastic net in linear regression, combining lasso and ridge strengths for improved model performance.
How to Use Lasso Regression: Example With Python
Improving linear regression with lasso regression models to reduce overfitting and perform feature selection.