Projects
![sentiments.PNG](https://static.wixstatic.com/media/84be3d_c0656e06677d4c2a9ac720a42ef37b0c~mv2.png/v1/crop/x_4,y_0,w_538,h_528/fill/w_226,h_222,al_c,q_85,usm_0.66_1.00_0.01,enc_auto/sentiments_PNG.png)
Sentiment Analyzer
​
Data Science Project.
​
Built a sentiment analyzer using the Natural Language Toolkit (NLTK) package, a commonly used NLP(Natural Language Processing) library in Python, to analyze textual data. Prepared a dataset of sample tweets from the NLTK package for NLP. Tested and trained the machine learning model on pre-classified tweets and used the model to classify the sample reviews into negative and positives sentiments.
Technology used: Python 3 (version 3.6.5)
Project Duration: 5 months
Problem Statement: In sentiment analysis we classify the polarity of a given text at the document, sentence, or feature /aspect level; whether the expressed opinion in a document, sentence or an entity feature/aspect is positive or negative.
Solution Approach: Sentiment analysis is the automated process of understanding the sentiment or opinion of a given text. This machine learning tool can provide insights by automatically analyzing product reviews and separating them into tags: Positive, Neutral, Negative
Key Benefits:
​
-
Sentiment analysis of product reviews helps improve customer service by tracking the key messages from customers' opinions and thoughts about a brand.
​
-
Developing Quality Products by analyzing customer opinions about a brand simplifies the process of maintaining customer loyalty and provides opportunities for improvement.
​​
-
With more data and information gathered through sentiment analysis, the organizations could develop an effective marketing strategy
​​
-
Improve Media Perceptions by tracking the understanding of the journalists, writers, columnists, market analysts, media researchers or independent contributors towards the company, be it the product, service, company values, human resources etc.
​​
-
Increasing Sales Revenue
​​
-
Frequent monitoring of the customers’ responses or opinions towards a brand would help to identify any issues quickly and improve crises management.​
​
![DoctorTap img.PNG](https://static.wixstatic.com/media/84be3d_d7e3185f5bad489fa9c8aeacab1a4e6c~mv2.png/v1/crop/x_2,y_0,w_424,h_418/fill/w_225,h_222,al_c,q_85,usm_0.66_1.00_0.01,enc_auto/DoctorTap%20img_PNG.png)
DoctorTap
​
UI/UX Design project.
​
Designed and built a working prototype of a multipurpose healthcare mobile application using Figma.
Technology Used: Figma
Project Duration: 2 weeks
Problem Statement: To book doctor's appointment and share patient's medical history online.
Solution Proposed: Enhance a user's experience at the hospital by building a multipurpose healthcare mobile application.
Key Benefits:
​
-
User can share their medical history with any new doctor that they are visiting. This information is stored within the app and can be shared by the patient using their QR code. This eliminates the need for carrying various documents that one might need when they decide to have a hospital visit.
​​
-
The second core function this app provides is the ability to book appointments at their desired hospital.
​​
-
Using this application, users can also keep a record of their symptoms if any so when the time comes to visit a hospital it is easier to give an account of their health condition to their doctor.​
​