Ameya Shanbhag

● Developing a robotic arm which rotates and revolves around its axis to perform various functions by using a special arrangement called “Selective Compliant Assembly Robot Arm(SCARA)”.
● Programming the arm in python and integrating it with Computer Vision using OpenCV to enable it to identify objects.
● Designed and integrated machine learning models which helped optimise the speed of the robotic arm.
● Technology Used: Image Processing, Computer Vision, Machine Learning.

--Used the movie_reviews dataset to train and identify all the positive and negative words using NLTK Library.
--Developed a voting classifier using various algorithms like Naive Bayes, Linear Regression, Logistic Regression and Support Vector Machine where my voting classifier will implement all the algorithms listed above on my testing set and gather votes/confidence score from each of the algorithms and accordingly judge whether the word is positive and negative.
--Real time streaming… Mehr zeigen

--Used the movie_reviews dataset to train and identify all the positive and negative words using NLTK Library.
--Developed a voting classifier using various algorithms like Naive Bayes, Linear Regression, Logistic Regression and Support Vector Machine where my voting classifier will implement all the algorithms listed above on my testing set and gather votes/confidence score from each of the algorithms and accordingly judge whether the word is positive and negative.
--Real time streaming of tweets was done with the help of Twitter API and the sentiment about a user specified topic was visualized.
Weniger anzeigen

● Designed a system which allows users to make investment decisions using predictive machine learning.
● Integrated Microsoft’s Language Understanding Intelligent System(LUIS) which was later on exported to Microsoft’s Cognitive Services which helped convert user’s speech to bot’s action.
● Developed a Two-Step Verification mechanism which ensured the security of the transactions carried out by the bot.
● Designed the structured flow of the conversation that the bot will make with the… Mehr zeigen

● Designed a system which allows users to make investment decisions using predictive machine learning.
● Integrated Microsoft’s Language Understanding Intelligent System(LUIS) which was later on exported to Microsoft’s Cognitive Services which helped convert user’s speech to bot’s action.
● Developed a Two-Step Verification mechanism which ensured the security of the transactions carried out by the bot.
● Designed the structured flow of the conversation that the bot will make with the user. Used ‘GupShup’ framework for designing of the bot.
● Integrated BAE Bank Bot with Facebook messenger, Skype, Telegram, Kik and Slack platforms.
● Technology Used: Javascript, Microsoft LUIS, Microsoft Cognitive Services.
Weniger anzeigen

Using historical data from previous applicants as a training set for logistic regression. For each training example, we have the applicant’s scores on two exams and the admissions decision.
Implementation of a classification model that estimates an applicant’s probability of admission based the scores from those two exams.

Regularised logistic regression to predict whether microchips from a fabrication plant passes quality assurance (QA). During QA, each microchip goes through various tests to ensure it is functioning correctly.
The product manager of the factory has the test results for some microchips on two different tests. From these two tests, he would like to determine whether the microchips should be accepted or rejected. To help him make the decision, a logistic regression model is developed using… Mehr zeigen

Regularised logistic regression to predict whether microchips from a fabrication plant passes quality assurance (QA). During QA, each microchip goes through various tests to ensure it is functioning correctly.
The product manager of the factory has the test results for some microchips on two different tests. From these two tests, he would like to determine whether the microchips should be accepted or rejected. To help him make the decision, a logistic regression model is developed using MATLAB. Weniger anzeigen

Prediction of House Prices taking size of the house,number of bedrooms as parameters with the help of Linear Regression Algorithm and Feature Normalisation on MATLAB.

● Developed an application to connect the customers with salons in their locality.
● Integrated Material Design Library for the user interface and JSON for parsing data from database.
● Implemented features for users to review any nearby salons and recommend them to their peers.
● Modeled separate account for registration of customers and vendors which were monitored by an Admin Account.
● Technology Used: Android, JSON

Its a static website made for an interior designing company which consists of all the information and the projects made by the company.

Basically,the idea was to list as many customers as possible on our maps so that people can have access to them on one click.I made a registration application for the "SELLERS" which would be beneficial to collect information and list them on our application.The application consists of the basic idea about the final application with a mobile verification so that the application wont be spammed.It even consists of category and sub-category list so that it will be easy for the sellers to get… Mehr zeigen

Basically,the idea was to list as many customers as possible on our maps so that people can have access to them on one click.I made a registration application for the "SELLERS" which would be beneficial to collect information and list them on our application.The application consists of the basic idea about the final application with a mobile verification so that the application wont be spammed.It even consists of category and sub-category list so that it will be easy for the sellers to get themselves listed. Weniger anzeigen

There has not been a single app on play store which is able to calculate CGPA of Mumbai university and majorly CGPA calculators take two inputs per subject which is tedious.In this app ,only one input is req. each subject and the CGPA is calculated.

● Developed a deep learning application which would take in any voice input, would convert the voice to Obama’s voice and create a video of
Obama saying the same thing you gave as a voice input but in Obama’s voice.
● Used transfer learning to convert a voice input to Obama’s voice input and used Deep Learning to train the model for Obama video generation

• Implemented Spark Streaming to fasten the ETL Process which enabled us to read files of different formats.
• Identified the AQI levels of different gases which are harmful for the atmosphere and analyzed the correlation between temperature,
deaths and pollution.
• Predicted the future temperature values based on pollution level using Decision Tree Classifier from Spark MLlib. and evaluated the
yearly effect of pollutants on number of Deaths for each disease.
• Plotting the real… Mehr zeigen

• Implemented Spark Streaming to fasten the ETL Process which enabled us to read files of different formats.
• Identified the AQI levels of different gases which are harmful for the atmosphere and analyzed the correlation between temperature,
deaths and pollution.
• Predicted the future temperature values based on pollution level using Decision Tree Classifier from Spark MLlib. and evaluated the
yearly effect of pollutants on number of Deaths for each disease.
• Plotting the real time twitter data streaming to monitor changes in sentiment with respect to climate change. Weniger anzeigen

• Predicted the temperature of a given city across a specific time period, using an ARIMA model for time series forecasting in Python.
• Analyzed the effect of greenhouse gases on temperature and predicted the greenhouse gas that will play a major role in temperature
change.
• Using Plotly, created an interactive visualization showing the top 10 cities that would experience the most temperature change in the
next decade.
• Determined the effect of greenhouse gases and pollution… Mehr zeigen

• Predicted the temperature of a given city across a specific time period, using an ARIMA model for time series forecasting in Python.
• Analyzed the effect of greenhouse gases on temperature and predicted the greenhouse gas that will play a major role in temperature
change.
• Using Plotly, created an interactive visualization showing the top 10 cities that would experience the most temperature change in the
next decade.
• Determined the effect of greenhouse gases and pollution on the temperature and explored the correlation matrix. Weniger anzeigen