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100-days-of-ml-code

100 Days of ML Coding

1806

18.06 course at MIT

30-days-of-python

30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace.

365-days-computer-vision-learning-linkedin-post

365 Days Computer Vision Learning Linkedin Post

500-ai-machine-learning-deep-learning-computer-vision-nlp-projects-with-code

500 AI Machine learning Deep learning Computer vision NLP Projects with code

all-of-statistics

Self-study on Larry Wasserman's "All of Statistics"

andrew-ng-notes

This is Andrew NG Coursera Handwritten Notes.

attention_keras

Keras Layer implementation of Attention

automatic_ticket_classification

You need to build a model that is able to classify customer complaints based on the products/services. By doing so, you can segregate these tickets into their relevant categories and, therefore, help in the quick resolution of the issue. You will be doing topic modelling on the <b>.json</b> data provided by the company. Since this data is not labelled, you need to apply NMF to analyse patterns and classify tickets into the following five clusters based on their products/services: * Credit card / Prepaid card * Bank account services * Theft/Dispute reporting * Mortgages/loans * Others  With the help of topic modelling, you will be able to map each ticket onto its respective department/category. You can then use this data to train any supervised model such as logistic regression, decision tree or random forest. Using this trained model, you can classify any new customer complaint support ticket into its relevant department.

automl

Google Brain AutoML

autoviz

Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

awesome-datascience

:memo: An awesome Data Science repository to learn and apply for real world problems.

awesome-longtailed-learning

A curated list of awesome deep long-tailed learning resources.

awesome-mlops

A curated list of references for MLOps

awesome-pipeline

A curated list of awesome pipeline toolkits inspired by Awesome Sysadmin

awesome-pytorch-tutorials

Awesome Pytorch Tutorials

awesome-streamlit

The purpose of this project is to share knowledge on how awesome Streamlit is and can be

bank_customer_segmentation

The repositeries involves the concepts of Clustering.

best-of-ml-python

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

books

Collections of Books | ML DL & AI Field

chatbot

cheatsheet-translation

Translation of VIP cheatsheets for Machine Learning Deep Learning, and Artificial Intelligence

classification_app

This app is developed to show the different stages of the classification problems in any machine learning projects.

codecarbon

Track emissions from Compute and recommend ways to reduce their impact on the environment.

collections-knowledge-sharing

I am Data Science Learner. I am Start preparing Data Science, AI & ML Knowledge Sharing which will helpful to all learners.

coursera-guided-projects-2021

Coursera Guided Projects 2021

credit_worthiness_check

Businesses or companies can fall prey to default if they are not able to keep up their debt obligations. Defaults will lead to a lower credit rating for the company which in turn reduces its chances of getting credit in the future and may have to pay higher interests on existing debts as well as any new obligations. From an investor's point of view, he would want to invest in a company if it is capable of handling its financial obligations, can grow quickly, and is able to manage the growth scale. A balance sheet is a financial statement of a company that provides a snapshot of what a company owns, owes, and the amount invested by the shareholders. Thus, it is an important tool that helps evaluate the performance of a business.

cs-video-courses

List of Computer Science courses with video lectures.

customer_analytics

This app makes a strategic decisions based on predictive analysis of customer data and its interpretation.

data-cleaning-and-exploration-with-machine-learning

Data Cleaning and Exploration with Machine Learning