skshiraj

AppliedAICourse

This repo has all the code files which were created as part of the assignments to complete the Applied AI Course. The credit for code source structure and data goes to the Applied AI team.

Backpropagation

CNN-ON-CIFAR-10-DATASET

A test accuracy of 90.04% was acheived by training the densenet model from scratch.There are no dropouts,no fully connected layers used.There are only 0.8 million parameters in total.

My_exp

Text_classification

text_classification using conv_1d

Transfer-Learning

11-Apply-Truncated-SVD-on-Donors-Choose-dataset-

13-Try-various-CNN-networks-on-MNIST-dataset-

14--LSTM-on-Donors-Choose

17-Microsoft-Malware-detection

23-Facebook-Friend-Recommendation

24-Apparel-Recommendation

25-CNN-on-CIFR

4-Apply-Naive-Bayes-on-Donors-Choose-dataset

5-Logistic-Regression-on-Donors-Choose-dataset

6-Implement-SGD-for-linear-regression

7-Apply-SVM-on-Donors-Choose-dataset-

9-Apply-Random-Forests-GBDT-on-Donors-Choose-dataset

AAIC

AAIC-case-studies-

CIFAR_CNN

downloads

Logistic-regression-using-SGD-withour-scikit-learn

LSTM_on_Donor_choose

This is a jupyter notebook which deals with three LSTM models on Donors choose dataset data can be found at :https://www.kaggle.com/c/donorschoose-application-screening/data

Machine-Learning-

Projects-casestudies and tasks of machine learning

Main

ML_Algorithms

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_aasignments

tensorflow-notebooks

This repo contains notebooks that helps in learning tensorflow. That includes various topics in deep learning and their implementations in Tensorflow