Pinned Repositories
Automatic-Indian-Sign-Language-Translator
Created an Automatic Translator, an application which is purposely deployed for deaf people that converts speech to text and then to Indian Sign Language gestures. Machine Translation and Natural Language Processing techniques are widely used.
Automatic-Indian-Sign-Language-Translator-ISL
I created an application which takes in live speech or audio recording as input, converts it into text and displays the relevant Indian Sign Language images or GIFs, using Natural Language Processing and Machine Learning Algorithm.
Classify-Song-Genres-from-Audio-Data
Rock or rap? Machine Learning methods in Python to classify songs into genres.
Comparing-Cosmetics-by-Ingredients
Process ingredient lists for cosmetics on Sephora then visualize similarity using t-SNE and Bokeh. Project
data-flow-diagram
Few of the Data Flow Diagrams are made available in this repository for reference and learning purposes. Generally Students/Developers study about this under course Software Engineering.
Extract-Stock-Sentiment-from-News-Headlines
Scrape news headlines for FB and TSLA then apply sentiment analysis to generate investment insight.
Java-Programming
CSE1007 Java Programming
One-Click-Launch-Infrastructure-Terraform-AWS
Launch complete infrastructure on AWS using Terraform with just one click. Launching of Instance and other services like EBS, S3 and many more with just one click and the bonus is, we’ll be able to delete the complete infrastructure with just one click too. Isn’t it amazing?
Predicting-Credit-Card-Approvals
Predicting Credit Card Approvals, Commercial banks receive a lot of applications for credit cards. Many of them get rejected for many reasons, like high loan balances, low income levels, or too many inquiries on an individual's credit report, for example. Manually analyzing these applications is mundane, error-prone, and time-consuming (and time is money!). Luckily, this task can be automated with the power of machine learning and pretty much every commercial bank does so nowadays. In this project, you will build an automatic credit card approval predictor using machine learning techniques, just like the real banks do. The dataset used in this project is the Credit Card Approval dataset from the UCI Machine Learning Repository.
satyaoil.github.io
Website for the company Satya Oil Field Services Pvt. Ltd. (Corporate Website)
satyam9090's Repositories
satyam9090/data-flow-diagram
Few of the Data Flow Diagrams are made available in this repository for reference and learning purposes. Generally Students/Developers study about this under course Software Engineering.
satyam9090/Java-Programming
CSE1007 Java Programming
satyam9090/Network-and-Communication
Data communications refers to the transmission of this digital data between two or more computers and a computer network or data network is a telecommunications network that allows computers to exchange data. The physical connection between networked computing devices is established using either cable media or wireless media. The best-known computer network is the Internet.
satyam9090/Operating-Systems
CSE2005 Operating Systems, Basic Linux Commands, IPC, Shared Memory, Scheduling Algorithm, Synchronization Problems, Deadlock: Bankers Algorithm, Memory Management, Paging and Segmentation
satyam9090/Predicting-Credit-Card-Approvals
Predicting Credit Card Approvals, Commercial banks receive a lot of applications for credit cards. Many of them get rejected for many reasons, like high loan balances, low income levels, or too many inquiries on an individual's credit report, for example. Manually analyzing these applications is mundane, error-prone, and time-consuming (and time is money!). Luckily, this task can be automated with the power of machine learning and pretty much every commercial bank does so nowadays. In this project, you will build an automatic credit card approval predictor using machine learning techniques, just like the real banks do. The dataset used in this project is the Credit Card Approval dataset from the UCI Machine Learning Repository.
satyam9090/A-Visual-History-of-Nobel-Prize-Winners
A Visual History of Nobel Prize Winners. The Nobel Prizes are widely regarded as the most prestigious awards given for intellectual achievement in the world. - britannica.com
satyam9090/course-resources-ml-with-experts-budgets
Further student resources for DrivenData's 'Machine Learning with the Experts: School Budgets' DataCamp course.
satyam9090/CV-tips-mistakes-frontend
satyam9090/Data-Base-Management-Systems
Most colleges have a number of different courses and each course has a number of subjects. Now there are limited faculties, each faculty teaching more than one subjects. So now the time table needed to schedule the faculty at provided time slots in such a way that their timings do not overlap and the time table schedule makes best use of all faculty subject demands. The existing algorithm is long and the process becomes tedious. Our algorithm aims to provide a hassle-free way to generate a timetable for the faculties by using only one pre-existing table from the faculty wish list and details about the courses. The administrators need not worry about time clashes and there is no need for him to perform any permutations and combinations. An effective timetable is crucial for the satisfaction of enormous requirement and the efficient utilization of human and space resources, which make it an optimization problem. By the common hit and trial method, a solution is not guaranteed. We use a priority based allocation method, which allocates courses to faculties based on their wish list. Keeping in mind the maximum and minimum credits to be allocated, and also taking into consideration the maximum number of subjects that can be allocated to each faculty, we assign the minimum credits to all faculties. Then moving as per the priority list, based on seniority, we assign the remaining courses to the faculties. This method ensures that all faculties are given the minimum credits required, according to their preference. Also, no courses are repeated for a faculty.
satyam9090/DataCamp_Solutions_Python
My solutions to DataCamp projects (now only Python)
satyam9090/documentation
Plotly's Documentation
satyam9090/Healer
satyam9090/Healthify
It’s no surprise that we are on a slippery slope when it comes to healthcare. With access and affordability to health insurance hanging in the balance, it’s more important than ever to take care of your mind, body and spirit.
satyam9090/Read-Write-Excel-Python
Using openpyxl module, one can retrieve information from a spreadsheet. For example, reading, writing or modifying the data can be done in Python. Also, user might have to go through various sheets and retrieve data based on some criteria or modify some rows and columns and do a lot of work.
satyam9090/Read-Write-Excel-Using-Python
Using xlrd module, one can retrieve information from a spreadsheet. For example, reading, writing or modifying the data can be done in Python. Also, user might have to go through various sheets and retrieve data based on some criteria or modify some rows and columns and do a lot of work.
satyam9090/TV-Halftime-Shows-and-the-Big-Game
DATA MANIPULATION | DATA VISUALIZATION | IMPORTING & CLEANING DATA | Whether or not you like football, the Super Bowl is a spectacle. There's drama in the form of blowouts, comebacks, and controversy in the games themselves. There are the ridiculously expensive ads, some hilarious, others gut-wrenching, thought-provoking, and weird. The half-time shows with the biggest musicians in the world, sometimes riding giant mechanical tigers or leaping from the roof of the stadium. The dataset used in this project was scraped and polished from Wikipedia. It is made up of three CSV files, one with game data, one with TV data, and one with halftime musician data for all 52 Super Bowls through 2018.