skshiraj Goto Github PK

microsoft_malware_detection

Microsoft malware detection multiclass classification model.

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 data mining to deep learning.

ml_algorithms

models

Models and examples built with TensorFlow

my-projects-arsenal

Here are the projects I worked on in machine learning and deep learning concepts under the guidance and supervision from Applied AI course. The programming language I've used is python.

my-sql

my_aasignments

my_exp

naive-bayes-donor-choose

Apply Naive Bayes on Donors Choose dataset

naive-bayes-on-donorschoose-dataset

Applying Naive Bayes on Donors Choose

naivebayes

Implementation of Naive Bayes Algorithm Using Donors Choose Dataset

netflix-movie-recommendation

Netflix Movie Recommendation

optionalassignment

Applied AI Course Assignments

pandas-exercises

This repository contains basic exercises for Pandas library.

papers

Summaries of machine learning papers

performanancemetrics

personalized-cancer-diagnosis

Personalized Cancer diagnosis

python-exercises-for-beginners

In this repository, you will find basic exercises for Python Beginners which are essentials for starting out in Data-science.

python_tutorial_ques

Complex Python programming practice questions without Scikit_Learn or numpy to hone skills for data science.

pythonbasics

Basic of Pyhton, Numpy, Matplotlib

pytorch-essential-training-deep-learning

FASHION MNIST and NEURAL NETWORKS

random-forest

random-forest-

For reference

random-forest---gbdt-on-decision-trees

Applying RF and GBDT on DonorsChoose Dataset

regression

It has a working comparison study between Linear regression and Support vector regression.

review-analyzer-nlp

Gvies the Polarity of review weather it is positive or negitive

rf_gbdt_dt_svm

This Repository contains Assignments regarding Random Forest, GBDT, Decision Trees and SVM

sep_03

sgd

Implementing Logistc Regression with L2 regularization Using SGD: without using sklearn

sgd-1