Skillocity - For All Your Skill Needs And Inquisitiveness!

Data science is spread across our lives and we are surrounded by its applications. We unknowingly use the vast number of applications of data science and machine learning such as recommender systems, house price prediction, data monitoring and data analysis etc. We are in fact surrounded by data and probably have played around with it many a times (especially if you're a math loving person). So here's another web app in yet another vital application of data science. This is a financial stock price web app. It shows the closing financial stock price values for S and P 500 companies. S and P 500 companies are 500 of the largest companies listed on stock exchanges in the US. The S and P 500 stock market index comprises of 505 common stocks issued by 500 large cap companies. The stocks of these companies trade either on the NYSE (New York Stock Exchange) or NASDAQ (National Association of Securities Dealers Automated Quotations). NYSE is an auction market whereas NASDAQ is a dealer

After a friend told me about the Streamlit library, I instantly started working on multiple data science related projects which not only increased my abilities in data science, but made me more adept with the use of programming languages such as Python, MATLAB and HTML. At the time of writing this article, users can only deploy 3 web apps on Streamlit from a particular account. But, if you request them you can potentially also deploy more web apps.  So coming onto this project, it's similar to the Iris Classification and Prediction Web App and this dataset is used as an alternative to the classic Iris dataset given by R.A. Fisher. It's a penguin classification and prediction web app. It successfully classifies and predicts the species of Palmer penguin based upon a number of user input features such as bill length, bill depth, body mass, flipper length etc. The prediction is also based upon the gender of the penguin and the island group (Bisoce, Dream and Torgersen) where it is

 Yes, you heard that right. We are back with more Machine Learning content and another web app (Yup, machine learning is definitely very cool). This app is similar to our first web app i.e. Diabetes Detector. This is another disease detection web app which detects if you have any cardiovascular diseases (CVD) based on certain features such as age, resting blood pressure, cholestrol, maximum heart rate achieved, ST depression induced by exercise and number of major vessels coloured by flouroscopy.  ST depression  refers to a finding on an electrocardiogram, wherein the trace in the  ST segment  is abnormally low below the baseline.  Fluoroscopy is an imaging technique that uses X-rays to obtain real-time moving images of the interior of an object.  This app is another example of the use of machine learning and data science in the field of medicine which I find very innovative.  This web app is based on machine learning and uses the Random Forest Classifier algorithm. The web app uses

Members of Skillocity are unique and talented in their own way. One of our team member, Roshan Kumar, has worked on a number of art and design projects and he's made multiple pieces of art which are undeniably brilliant. He has also participated in and won multiple art contests here in India. I have personally been following his art since the past few years and he is very impressive at it. Following are some of his drawings. We'll keep updating this page for as long as he provides us with more of his projects.  Created by: Roshan Kumar, Creator at Skillocity

  One of my primary interests in the field of computer science is Machine Learning. Machine Learning has no bounds and here, the sky is not the limit. It has applications in many important sectors such as biotechnology, medicine, aviation etc. This is my second web app on Machine Learning and I'm working hard to successfully deploy many more Machine Learning apps. All of these projects are free to use and I welcome any suggestions and/or additions to the project.  One of the main reasons why I love Machine Learning is that it perfectly incorporates the beauty of mathematics and computer science to successfully integrate and develop a particular application. As I mentioned in the previous article, Machine Learning not only requires a good understanding of coding, it also requires in depth knowledge in Maths. So for the people out there who question the use of Maths in Computer Science, this is a classic example as to why that's not always the case. Having a good knowledge about