mayurmahurkar Goto Github PK

machine-learning-curriculum

Complete path for a beginner to become a Machine Learning Scientist!

machine-learning-interview-questions

This repository is to prepare for Machine Learning interviews.

machine-learning-mindmap

A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.

machine-learning-with-python

Study Material for Machine Learning with Python

machine-learning-with-python-cookbook-notes

(Part of) Chris Albon's Machine Learning with Python Cookbook in .ipynb form

manim

Animation engine for explanatory math videos

mayurmahurkar

mec-mini-projects

metal-defect-detection

Detection and Segmentation of Manufacturing Defects with Convolutional Neural Networks and Transfer Learning

ml-from-scratch

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

ml_telecom_churn

Machine Learning Telecom Churn Model

mltutorial

Machine Learning Tutorial in IPython Notebooks

mml-book.github.io

Companion webpage to the book "Mathematics For Machine Learning"

mtcnn_face_detection_alignment

Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Neural Networks

opencv-face-recognition

Real-time face recognition project with OpenCV and Python

pandas-in-action

Complete source code (datasets and Jupyter Notebooks) for Pandas In Action

pandas_exercises

Practice your pandas skills!

pbpython

Code, Notebooks and Examples from Practical Business Python

power-bi

Here, I will provide different Power BI Sample files and data source files to user.

powerbi-visuals-barchartrace

The familiar bar chart turns fascinating with a new trendy feature to animate bars racing to the top based on ranks, in Power BI.

practical-machine-learning-with-python

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

python-for-probability-statistics-and-machine-learning

Jupyter Notebooks for Springer book "Python for Probability, Statistics, and Machine Learning"

python-machine-learning-book-3rd-edition

The "Python Machine Learning (3rd edition)" book code repository

python-oops

Basics of Python's OOPs concept and Classes, Sub-classes.

python_for_microscopists

https://www.youtube.com/channel/UC34rW-HtPJulxr5wp2Xa04w?sub_confirmation=1

simpleitk-notebooks

Jupyter notebooks for learning how to use SimpleITK

skimage-tutorials

skimage-tutorials: a collection of tutorials for the scikit-image package.

stanford-cars-body-data

The data consist of images of cars categorised according to their body type. I've created this data from the "train" subset of the actual data provided in Standford's Cars Dataset (http://ai.stanford.edu/~jkrause/cars/car_dataset.html). For this, I've used "class" info as given for each car image but only for "train" data. The "class" in actual data is car name, from which I've extracted body types such as hatchback, sedan, SUV etc. and made them as classes in this dataset. For convenience, I've renamed the actual file_name with the "class" as mentioned in the actual dataset. The "standford_cars_type.csv" can provide you additional detail about the name and manufacturer along with the original name of the image as in the "train" subset of Stanford's Cars Dataset as mentioned above. This data can be used for building: - Car Body Type Classifier - Car Brand Classifier (You have to recreate the data for "Car Brand Classifier" accordingly. NOTE: The "Other" subfolder in the dataset consists of images of "SuperCab" which can be either used as an additional class or can be merged in the existing "Cab" class.

stanford-cs-230-deep-learning

VIP cheatsheets for Stanford's CS 230 Deep Learning

start-machine-learning-in-2020

A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2021 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques!