This skills contains dynamic content: It gives user some random fact, with invocation: "some facts"
Invocation name: some facts

• "Alexa some facts"
• "Alexa give me a fact"
• "Alexa give me fact on statue of unity"

This skills contains dynamic content: some random interesting facts
Invocation name: interesting facts

• "Alexa interesting facts"
• "Alexa give me a fact"
• "Alexa useful fact"

The goal of the project was to analyze historical data about Starbucks' app usage in order to develop an algorithm that finds the most suiting offer type for each customer.

This project provide with result in a simple web app which interacts with a deployed recurrent neural network (RNN) performing sentiment analysis on movie reviews. This project assumes some familiarity with SageMaker.

In this project, I have build a plagiarism detector that examines a text file and performs binary classification; labeling that file as either plagiarized or not, depending on how similar that text file is to a provided source text. Detecting plagiarism is an active area of research; the task is non-trivial and the differences between paraphrased answers and original work are often not so obvious.

In this project, I have perform Exploratory data analysis on how the different features of a car and its price are related. The data comes from the Kaggle dataset "Car Features and MSRP". It describes almost 12,000 car models, sold in the USA between 1990 and 2017, with the market price (new or used) and some features.

I have build and train a convolutional neural network (CNN) in Keras from scratch to recognize facial expressions. Test data used, consists of 48x48 pixel grayscale images of faces to classify each face based on the emotion. I have used here seven facial expression (Angry, Disgust, Fear, Happy, Sad, Surprise, Neutral). Used OpenCV to automatically detect faces in images and draw bounding boxes around them. After training, saving, and exporting the CNN, one can serve the training model predictions to a web interface and perform real-time facial expression recognition on video and image data.

Built an Android based “Calculator” app which can perform all basic mathematical operations. The app doesn't require any special permission from the device. One can install this app in your smartphone by downloading the Api for the same. For downloading please refer the README.md

Build on 2-pass algorithm modified to 1-pass with MDI & further modified with 1-pass with stack Improved the cases handling in the modified algorithm

• algo1: It consists of pass-1 and pass-2 algorithm (pass-1 processing macro definition; pass-2 processing macro calls and expansion)
• algo2: It consists of Algorithm 2---Simple one-pass macro processor
• algo3: It consists of Algorithm 3---One-pass macro processor capable of handling macro calls within macro definitions

• Works for nth - Level Nested Macro Call and Definition.
• Uses 2-D array for Argument and Line Numbers (such as argument - 'ARGU1', line number - 95)
• It recognize difference between Upper Case and Lower Case.
• It has all the functionality of Algorithm 1 and 2 of Macro Processor.
• It is Backward referencing software.

Built a website based on educational theme as part of competition conducted by Progate. Created a static website with functional links for social site, sign in, sign up, links for the tutorial. Created using HTML5, CSS, JavaScript.

Conducted a sample survey on facilities in Banasthali Vidyapith as a part of Certificate course in Statistical Techniques and Applications.