Deep learning using CNN in tensorflow on Kaggle image dataset containing 87,900 different healthy and unhealthy crop leaves spanning 38 unique classes.

A notebook about commonly used machine learning algorithms.

A series of Jupyter notebooks, to know about Machine Learning, its implementation, and identifying its best practices.

Deep learning Projects

This repository contains hands-on Jupyter notebooks that explore key concepts in machine learning, such as logistic regression, regularization, dimensionality reduction, clustering, and more. Each notebook is designed to explain core ideas through practical examples and datasets.

Notebooks in Machine Learning. Including exponential, polynomial, logistic and softmax regression. Time series analysis. Neural Networks.

In this repo I working on various Machine Learning Algorithms.

Notebooks developed in Mathematica for my Ph.D. thesis and other resources

Notebooks explaining various Machine Learning concepts.

Jupyter notebooks implementing Deep Learning algorithms in Keras and Tensorflow

Notebooks of programming assignments of Improving Deep Neural Networks course of deeplearning.ai on coursera in August-2019

A complete and in-depth machine learning resource containing detailed notes, mathematical explanations, Python code, and Jupyter notebooks., and lectures.

Github repo for ML Specialization course on Coursera. Contains notes and practice python notebooks.

This repository contains a Jupyter notebook that implements Linear Regression using Gradient Descent from scratch. The notebook also includes a comparison of the results with the scikit-learn implementations of Linear, Lasso, and Ridge Regression by plotting graphs.

A collection of Jupyter Notebooks covering Regression, Classification, Neural Networks, Decision Trees, and ML Best Practices with hands-on implementations using Scikit-Learn, TensorFlow, and XGBoost.

5 courses of Specialization in Deep Learning taught by Prof.Andrew Ng on Coursera

Convolutional network for image classification of brain tumors into categories: glioma, meningioma, no tumor, pituitary. Built using Tensorflow. If you want to observe the Kaggle notebook, use the provided for the repo.