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Name: Shrikrishna Parab

Type: User

Bio: Full Stack Developer turned Data Scientist. Has a BE in IT along with Masters's (MTech) in CS. Works in Data Science, Analytics, NLP, Machine Learning, DL

Location: Goa, India

Blog: https://shrikrishnaparab.tech/

Hi, I'm Shrikrishna Parab!

I am a Data-Driven, Passionate Data Scientist and Machine Learning Enthusiast

Data has always fascinated me. My passion for uncovering insights and answering complex questions with the help of data has led me to the field of Data Science.

I earned a Diploma in Electronics and Communication in 2010, and subsequently completed a Bachelor of Engineering (BE) in Information Technology in 2013 and worked as a PHP developer. Afterward, I achieved a Master of Technology (MTech) degree in Computer Science in 2016, with a specialization in Natural Language Processing (NLP). I also gained valuable experience in Deep Learning, NLP and Information Retrieval by completing an internship under the mentorship of Dr. Pushpak Bhattacharyya at the Center for Indian Languages and Technology at IIT Bombay.

Motivated by my passion for tackling new and challenging problems, I founded an IT startup in the service sector in 2016. My startup focused on assisting various businesses in the tourism industry to scale their operations using cutting-edge technologies and innovative solutions. In my role as a founder, I was responsible for handling end-to-end projects for clients, utilizing various new technologies as per their requirements. This included everything from project management, coding, and documentation throughout the entire project lifecycle.

After shouldering the responsibilities of a founder and honing my skills as a Full-Stack Developer(MERN Stack, Django) for five years in my startup with many ups and downs, my passion for data science has drawn me back to the field. I am excited to apply my experience and skills to analyze and interpret complex data, uncover valuable insights and develop data-driven solutions.

👉 I’m interested in Data Science, Data Analysis, Machine Learning, Deep Learning, Natural Laguage Processing and Web Development
🔨 I'm currently working on some interesting Natural Laguage Processing and a predictive analysis project.
🌱 I'm currenly also learning Google Cloud Platform (GCP).
🤝 I’m open to collaborating on usefull applications which will solve some real life problems.
💻 As a proffesional I aspire to make things that improve lives, so feel free to contact me if that's your goal as well.

Things I use:

📫 How to reach me (right click for new window):

You can also visit my webiste at: shikrishnaparab.tech

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Go and enjoy the rest of your day! 🤜🤛

Shrikrishna Parab's Projects

article-recommendations-to-user

Article Recommendations to user

basic-classification-using-k-nearest-neighbors-knn

Basic Classification using K Nearest Neighbors KNN

chat-analyzer

This project is a Data Analysis project to analyze the WhatsApp chats.

cloudnotes

CloudNotes is a MERN stack app for creating notes and saving it on the cloud.

duplicate-question-predictor

The ipython notebook is working to build a model which will detect duplicate questions if two questions pair are given.

expo_backend

expodb_backend

face-detection-using-mtcnn-and-opencv

Face Detection using MTCNN and OpenCV

fifa-wc-2022-qatar-data-analysis-eda

This is a Jupyter Notebook( iPython Notebook) with Data Analysis (EDA) on FIFA WC Qatar 2022 match data.

flipkart-laptops-analysis-eda

This ipython notebook is the Exploratory data analysis (EDA) of the Laptops listed on Flipkart.

fullstack_sql

Full stack CRUD application using ReactJs on the client side and NodeJs ExpressJS on the Server side with MySql database.

gender-prediction-based-on-name-lstm

this ipython notebook is working to build a model which will predict the gender based on the names.

generate_itinerary

gonews

This is a react app using class based component. This web app is a news portal which keeps you updated with what is happening around. This app uses newsdata.io api to fetch news articles and show it on the app.

gpt-build-itinerary

handwritten-digit-recognition

In this iPython Noetbook we are going to use the MNIST dataset for the implementation of a handwritten digit recognition app using LogisticRegression and SGDClassifier and compare the accuracy and other metrics.

heart-attack-analysis-prediction-accuracy-85.24

This iPython Notebook implements the Analysis and Predictions for Heart Attack. The Analysis is done on the dataset to identify the key features which has a impact on Heart Attack. After the analysis and data cleaning, the dataset is used to train the model using different ML algorithm.