nimitkothari Goto Github PK

11k-hands

3dgan-keras

Keras implementation of 3dgan

a_guide_to_running_tensorflow_models_on_android

This is the code for"A Guide to Running Tensorflow Models on Android" By SIraj Raval on Youtube

ai_for_business_curriculum

This is the curriculum for the "AI for Business" Course By Siraj Raval on Youtube

ai_in_finance

This is the code for "AI in Finance" By Siraj Raval on Youtube

ai_software_dev

Main repository for my AI and software development work.

ai_supply_chain

This is the code for "AI for Supply Chain" by Siraj Raval on Youtube

analytics

python data with cetification

anomaly-xray-gans

Anomaly detection on X-Ray MURA dataset using GAN.

anomaly_detection_with_autoencoder

automated-job-resume-matching-solution

According to a 2015 study on job seeking behavior by Pew Research Center, 79% of the job seekers utilized the online resources for their most recent employment (Aaron ,2015). This study result suggests that the online job boards become the major channel for job seekers in the digital era. However, another finding in the study indicates that most of the job seekers fail to match their experiences with the job requirements and spend hours on job board to apply job which is not seen to be suitable (Aaron, 2015). Additionally, Dr. John Sullivan conducted a similar research in 2013 which highlighted some interesting aspects: on average, 250 resumes are received for each job opening by the major organizations, more than 50% of the resumes does not meet the minimum requirement (John, 2013). This means the time our recruiter spends on these 50% of the resumes for each job is wasted. From both candidate and recruiter’s points of view, the phenomenon may suggest that the traditional online job board does not seem to simplify the job application process or reduce the effort required from both parties. With this challenge getting bigger and bigger, the demand to automate the resume - job matching process is getting increased as well. For instance, the content - based recommendation system (CBR) is introduced to analyze the job description to identify the potential area of interest to the job seekers (Shiqiang et al., 2016). To apply the concept in Singapore local context, our team has conducted a text mining project based on the data acquired from the major online job board in Singapore. The primary objective of this project is to create a machine learning model to accelerate the job - resume matching process. The detail of the text mining methodology and results are presented in the following sections.

automated-resume-screening-system

Automated Resume Screening System using Machine Learning (With Dataset)

automatic-pickle

automatic-pickle-app

awesome-quantum-machine-learning

Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web

backorder-prediction

Personal Data Analysis project of Backorder Prediction using Kaggle dataset

backorder-prediction-1

Machine Learning Application for backorder prediction using over sampling and class imballance handelling.

backorder_prediction

Predicting Backorders in Inventory Mangement Context.

bckup

blockchain

capgeminihackathon

classification_backorderprediction_project

Personal Data Analysis project of Backorder Prediction Kaggle dataset

comp

React Vue Angular1 Angular2 Utilize Virtual DOM Utilize Virtual DOM Utilize actual DOM * Provide reactive component Provide reactive component Performance Rendering time is more 1.Rendering time is less (transperent Dependency tracking.) 2.ahead of angular 2 As per 3 rd party framework. Performance is not better than any other framework. (lot of watchers.) Rendering time is slower than vue. Html & CSS Uses fusion of html,css & javascript. Also uses JSX. Uses simple html css. No need of advance version of javascript Uses html & css with Typescript Then compies to javascript. Uses html & css with Typescript Then compies to javascript. Scale support scaling up & down. But it takes time & resources to scale support scaling up & down. It takes less time & Resources. Native rendering Supports & can use the same components in android ,ios. Supports & can use the same components in android ,ios but in developing phase. Flexibility & modularity More flexible than angular1. Less than vue Less flexible than vue(less opinionated with vue.) Data binding One way(easier for non trivial applications) Two way Two way Directives vs components Clear differentiation No clear differentiation No data Learning Curve Require various pre requisite for developing appn. Easy for non trivial applications Require various pre requisite for developing appn. Require various pre requisite for developing appn. Complexity More than vue(API & Design) TypeScript * Large enterprise applications Large enterprise applications Only used for smaller applications. Large enterprise applications

conditional-molecular-design-ssvae

coursera-ibm-deep

covid-chestxray-dataset

We are building an open database of COVID-19 cases with chest X-ray or CT images.

crewai-mlcode-generation

custom-machine-learning

cvbankas-job-post-classification

Automatic cvbankas.lt web site job post classification into categories

data