Nishant Sharma's repositories
Credit-Risk
Applied Data Science for Credit Risk
certified-aws-developer-associate-notes
2023 AWS developer associate exam
Neural-Networks-Demystified
Supporting code for short YouTube series Neural Networks Demystified.
python-mastery
Advanced Python Mastery (course by @dabeaz)
Stress_Detector
API to detect Stress through real-time facial recognition using Deep learning and CNN
python-training
Python training for business analysts and traders
the-algorithm_twitter
Source code for Twitter's Recommendation Algorithm
Data-Science-Interview-Preperation-Resources
Resoruce to help you to prepare for your comming data science interviews
The-Kaggle-Book
Code Repository for The Kaggle Book, Published by Packt Publishing
it-cert-automation-practice
Google IT Automation with Python Professional Certificate - Practice files
Web-Application-Development-with-Streamlit
source code
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.
digital-data-scientist-hiring-test-powered-by-hackerrank
A few interesting data science problems along with my solutions in R and Python
deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Facial-Emotion-Recognition-using-CNN
A deep learning and image processing project used to predict the emotions of a person in image.
mit-deep-learning-book-pdf
MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville
Chapter3
Chapter 3: Text and Speech Basics
Chapter2
Chapter 2: Machine Learning Basics
Speech-Language-Processing
Code developed following Dr. Jurafsky's Book
practicalAI
📚 A practical approach to learning and using machine learning.
Python
All Algorithms implemented in Python
awesome-public-datasets
A topic-centric list of HQ open datasets. PR ☛☛☛
Data-Science--Cheat-Sheet
Cheat Sheets
Machine-Learning-Projects
Machine Learning Experiments and Work
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).
deeplearning
Python implementation of Deep Learning book
facebook-group-scrape-python
Beginner project scraping a private facebook group with python