AutoML (H2O) Project – A Guide to build a multi-class classification model in Python using OpenML dataset.
PyCaret Machine Learning Project – A Guide to build a Regression model in PyCaret using Dimond price dataset.
AutoKeras Project in Finance – A Guide to build a deep learning model in Python using in-vehicle coupon recommendation Data.
AutoML (H2O) Project for Finance – A Guide to build a classification model in Python using Loan Approval data.
AutoML (H2O) Project – A Guide to build a classification model in Python using IRIS data.
Types of Learning – Supervised Learning What is Learning for a machine? A machine is said to be learning from past Experiences(data feed in) with respect to some class of Tasks, if it’s Performance in a given Task improves with the Experience.For example, assume that a machine has to predict whether a customer will buy a specific product lets …
How to apply LightGBM Classifier to yeast dataset LightGBM is a powerful machine learning library that can be used to improve the performance of decision tree models. It is particularly useful for large datasets and datasets with a lot of features. In this essay, we will be discussing how to use the LightGBM …
How to apply CatBoost Classifier to yeast dataset CatBoost is a powerful machine learning library that can be used to improve the performance of decision tree models. It is especially useful for datasets with categorical features and is known for its ability to handle missing data and categorical features automatically. In this essay, …
Image classification using RandomForest: An example in Python using CIFAR10 Dataset Image classification is a task of assigning a label to an image based on its visual content. It is a fundamental problem in the field of computer vision and has many practical applications, such as self-driving cars and image search engines. One …
Image classification using LightGBM: An example in Python using CIFAR10 Dataset Image classification is a task of assigning a label to an image based on its visual content. It is a fundamental problem in the field of computer vision and has many practical applications, such as self-driving cars and image search engines. One …
Image classification using GradientBoost: An example in Python using CIFAR10 Dataset Image classification is a task of assigning a label to an image based on its visual content. It is a fundamental problem in the field of computer vision and has many practical applications, such as self-driving cars and image search engines. One …
Deep learning is a type of machine learning that uses neural networks with multiple layers, called deep neural networks, to analyze and understand complex data, such as images, speech, and text. In this essay, we will be discussing how to set up a deep learning model using Keras, a popular open-source library for …