nsh-786 Goto Github PK

awesome-public-datasets

A topic-centric list of HQ open datasets. PR ☛☛☛

certified-aws-developer-associate-notes

2023 AWS developer associate exam

chapter2

Chapter 2: Machine Learning Basics

chapter3

Chapter 3: Text and Speech Basics

classification-of-japanese-population-using-individual-as-well-as-stacked-models

credit-risk

Applied Data Science for Credit Risk

data-science--cheat-sheet

Cheat Sheets

data-science-interview-preperation-resources

Resoruce to help you to prepare for your comming data science interviews

datascience-lab7

Explored ensemble learning techniques including bagging, boosting, and stacking. Then make classification predictions using basic Random Forest, k-Nearest Neighbors, SVC, and Logistic Regression models.

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

deeplearning

Python implementation of Deep Learning book

digital-data-scientist-hiring-test-powered-by-hackerrank

A few interesting data science problems along with my solutions in R and Python

facebook-group-scrape-python

Beginner project scraping a private facebook group with python

facial-emotion-recognition-using-cnn

A deep learning and image processing project used to predict the emotions of a person in image.

it-cert-automation-practice

Google IT Automation with Python Professional Certificate - Practice files

machine-learning-projects

Machine Learning Experiments and Work

mit-deep-learning-book-pdf

MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville

neural-networks-demystified

Supporting code for short YouTube series Neural Networks Demystified.

practicalai

📚 A practical approach to learning and using machine learning.

python

All Algorithms implemented in Python

python-mastery

Advanced Python Mastery (course by @dabeaz)

python-training

Python training for business analysts and traders

speech-language-processing

Code developed following Dr. Jurafsky's Book

stress_detector

API to detect Stress through real-time facial recognition using Deep learning and CNN

super-learner-ensemble

The Super Learner is a heterogeneous stacked ensemble classifier. This is a classification model that uses a set of base classifiers of different types, the outputs of which are then combined in another classifier at the stacked layer. The Super Learner was described in (van der Laan et al, 2007) but the stacked ensemble idea has been around for longer than that - for example (Wolpert, 1992).

the-algorithm_twitter

Source code for Twitter's Recommendation Algorithm

the-kaggle-book

Code Repository for The Kaggle Book, Published by Packt Publishing

web-application-development-with-streamlit

source code