prashant-tariwal Goto Github PK

advanced-regression

bike-sharing-assignment

Case_study

boosting

course

cpython

The Python programming language

decision-tree-example

gesture_recognition

The objective of this project is to identify the hand gestures to control Smart TV.

house-price-prediction

Ridge and Lasso Regression - A US-based housing company named Surprise Housing has decided to enter the Australian market. The company uses data analytics to purchase houses at a price below their actual values and flip them on at a higher price. For the same purpose, the company has collected a data set from the sale of houses in Australia.

house_price_prediction

Assignment

lending_club_study

Prashant and Rajesh

linear-regression

logistic-regression

mlops

MLOps examples

mlops-lead-scoring-assignment

models

Models and examples built with TensorFlow

mri-styletransfer-cyclegan

CycleGAN, a variation of GAN (Generative Adversarial Network) which works well with unpaired data thus fits best for medical images. Used CycleGAN for T1-weighted to T2-weighted in MRI image translation.

mri_t1_t2_cyclegan

This project uses an unpaired dataset consisting of TN1 and TN2 MRI scans of the brain to train a deep learning model to convert TN1 into TN2 scans and vice-versa. CycleGAN technique have been used for the unpaired image translation application.

naive-bayes

named_entity_recognition_healthcare_data

Named Entity Recognition in Healthcare data to identify possible diseases and their suggested treatments from a corpus of medical text containing both disease and treatment.

neural-networks-project-melanoma-detection

Assignment

nlp

In this segment, you will use the IMDB movie reviews dataset to classify reviews as 'positive' or 'negative'. We have divided the data into training and test sets. The training set contains 800 positive and 800 negative movie reviews whereas the test set contains 200 positive and 200 negative movie reviews.This was one of the first widely-available sentiment analysis datasets compiled by Pang and Lee's. The data was first collected in 2002, however, the text is similar to movies reviews you find on IMDB today. The dataset is in a CSV format. It has two categories: Pos (reviews that express a positive or favourable sentiment) and Neg (reviews that express a negative or unfavourable sentiment). For this exercise, we will assume that all reviews are either positive or negative; there are no neutral reviews. You will need to build a Multinomial Naive Bayes classification model in Python for solving the questions.

numpy

The fundamental package for scientific computing with Python.

oops_project-url_shortner-

opencv

Open Source Computer Vision Library

opencv-python

Automated CI toolchain to produce precompiled opencv-python, opencv-python-headless, opencv-contrib-python and opencv-contrib-python-headless packages.

pandas-profiling

Create HTML profiling reports from pandas DataFrame objects

portfolio

Minimal is a Jekyll theme for GitHub Pages

practice

Testing Github

practice_upgrad

Practice

pytorch-cyclegan-and-pix2pix

Image-to-Image Translation in PyTorch