tanvirnwu Goto Github PK

basics-of-apis

brain--tumor--classification

Brain Tumor Classification using Pytroch and Tensorflow Transfer Learning Approach.

cheatsheet

codespacesportfolio

feature-engineering--python

feature-selection--python

"A set of Jupyter Notebooks on feature selection methods in Python for machine learning. It covers techniques like constant feature removal, correlation analysis, information gain, chi-square testing, univariate selection, and feature importance, with datasets included for practical application.

interview-questions

machine-learning-books

Collection of all Machine Learning Related Books

matplotlib--python

This repository is a learning resource for data visualization in Python using Matplotlib. It contains a series of Jupyter Notebooks, each dedicated to a different type of plot or visualization technique, including line plots, bar charts, histograms, pie charts, scatter plots, stack plots, and many more.

ml-algorithms--scikit-learn--python

This folder contains the basic algorithms of ML implemented with Python.

neural-networks--keras

numpy--python

opencv

A curated collection of Python scripts exploring the basics of OpenCV for image processing, including operations like blurring, edge detection, and color space transformations.

opengl--computer-graphics-basics

pandas--python

A collection of Jupyter Notebooks for learning and practicing data manipulation and analysis in Python using the Pandas library. The repository includes a series of notebooks designed to guide users from basic to more advanced features of Pandas. It also includes a CSV dataset related to Ethereum cryptocurrency for practical exercises.

python--basics

Contains some fundamental codes of Python.

pytorch--python

A repository of Jupyter notebooks showcasing a range of PyTorch applications, from foundational concepts and linear regression to neural network models for image classification tasks.

removing-symbols-variables-and-comment-from-codes-using-cpp

scikit-learn--python

seaborn--python

This repository is a comprehensive tutorial for creating statistical visualizations in Python using the Seaborn library. It includes a series of Jupyter Notebooks tailored to different types of plots, such as categorical, distribution, matrix-based, and regression visualizations.

selective-search-for-object-detection

This repository provides a Python implementation of Selective Search for object detection. It includes code for segmenting an image using the Felzenszwalb method, extracting candidate regions for object detection, and visualizing these regions.

skills-code-with-codespacess

My clone repository

tanvirnwu