ansh3101/machinelearning

Machine Learning Modelling On Regression & Classification Problems

Hey!

About

Hi! I'm Anshuman Tekriwal. I enjoy working on Artifical Intelligence - Machine Learning And Deep Learning

I use Python And R for Machine Learning while I use the PyTorch framework for Deep Learning (I am also comfortable with Tensorflow, which I prefer for simpler problems).

🏅 Achivements

• Finalist at the Artificial Intelligence International Junior Contest (2nd in the AI In Geoservices track)
• I was also a finalist for the National Technological Olympiad 2021-22 (Artificial Intelligence track)
• I also finished in the Top 30 at the Uber Global Hackathon 2022 in the Coding Department (Theme: Global Healthcare)

🔧 Technologies And Tools

📃 Repositories

Papers

Basic Implementations Of Some Of The Most Significant Papers Published In Reference To The Advancement Of Deep Learning

• LeNet

• VGG

• GoogLeNet

• ResNet

• LinearGAN / PrimitiveGAN

• DCGAN / ConvolutionalGAN

  • DigitGAN

  • FaceGAN

MachineLearning

Regressors, Classifiers & Perceptrons Implemented On Simple As Well As Intricate Datasets

• Helper Function

• Linear Regression

• Logistic Regression

• Decision Trees

Algorithms

Data Structures & Algorithms Implemented In C++ & Python

• Basics

• Pattern Writers

AIIJC

Codebase For Team CSPDarknet53's Interpretation Of The AI In Geoservices Challenge From The Artificial Intelligence International Junior Contest

Eye.AI

The Code Repository For Eye.AI: An Initiative To Detect Diseases Even In The Most Under-developed Regions

📇 Contact Me

E-Mail:

    [email protected]
    
    [email protected]

Discord:

    ansh3101

📈 Statistics

PROFILE VIEWS -

CONTRIBUTIONS -

machinelearning's Issues

To Do

Upcoming Simple Applications

Regression

• Polynomial Regression (Non-Linear)
• Perceptrons
• Naive Bayes
• Support Vector Regressors
• Decision Tree Regressors
• Random Forest Regressors
• CatBoost Regressors
• XGBoost Regressors
• LightGBMs

Classification

• Linear Discriminant Analysis
• Multi Layered Perceptrons
• Naive Bayes Classification
• K-Nearest Neighbour
• Support Vector Classifiers
• Decision Tree Classifiers
• Random Forest Classifiers
• CatBoost Classification
• XGBoost Classification
• LightGBMs

Implementations

• Wealth Index
• Trailblazers

Always Looking For More Suggestions!