About

"Hello World!"

Can we even imagine today’s life without numbers? A big ‘No’, Right? Numbers have the capability to extract hidden untold stories. I love numbers, I love Math & to be creative with them. Hence, my passion for data science landed me in the course of Artificial Intelligence & Data Science. Before that, I worked at Reliance Industries Limited, Hazira Manufacturing Division as a Manager for 3 years where my major job role included manpower management, Daily planning & prioritize of the job, SAP for material management, and Critical thinking to improve production efficiency. One of the major projects I worked on was to build an Oxygen line to supply oxygen to Surat city from the plant during the covid time. We did it within just 2 days which was a proud moment for us. During AI & DS, I learned various subjects such as Deep Learning, Machine learning, Probability & Statistics, Natural Language Processing, Computer Vision, Database & Data warehouse, and Data visualization. At present, I’m also working on research related to the Entropy function in Decision trees. Apart from academic life, I’m a cyclist,I love to play piano, football, chess & meditation.

I always wanted to work for humanity, which can improve lifestyle of not only humans but every living being. In my view, no other fields can do better job than data science when it comes to productivity of life. Hence, I felt this field is best alignment of my passion & my life goal. I’m very curious & excited to implement my knowledge to industry.

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Project Summary

Let's talk about some of my work related to coding. I have completed several projects that have fueled my passion for Data Science. Some of them were particularly interesting to me. I would like to share my journey of working on these projects, starting from the beginning. Let's dive into the fun zone!

BASKETBALL GAME ANALYSIS

This was one of the first projects I completed while studying Python. I collected and created the dataset from available data. The insights gained from this project helped me understand the importance of data science and how it can reveal valuable information that would otherwise go unnoticed.

Major Learning: Matplotlib,Numpy, User Define Functions

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Demographicdata ANALYSIS

In this project, I developed my skills in working with DataFrames. The data included various features such as Birth Rate, Internet Users, and Income Group. I utilized the Seaborn library to visualize the data and gain insights.

Major Learning: Pandas,Seaborn,boxplot,lmplot

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Movie Rating Analysis

This project involved an analysis of movie ratings in relation to genre, release year, and budget. I also identified the preferences of different groups of audiences for specific types of movies.

Major Learning: FacetGrid,Coordinates & Diagonals,violinplot,subplots,kdeplot

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Tic-Tac-Toe

The 2-Player Tic-Tac-Toe Game project is a computer program that allows two players to play the classic game of Tic-Tac-Toe against each other. It features a command line or graphical interface, programming concepts like loops, conditional statements, and functions and also include the ability to reset the game.

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Curved Space Algorithm

Gradient Descent Algorithm! One of most used & my favorite algorithm.

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Avg Distance Between 2 Points(in N-Dimensions)

The screenshot is from the famous book "HandsOn ML with SkLearn, Keras & TensorFlow".I was reading this book & I came to this paragraph. It was tough to visualize these numbers & I found it counterintuitive! Hence, I started the laptop & tried to code it. I got the exact average distance between 2 points in 1,000,000 dimension space 408.25 units! Such an Aha moment!

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COVID 19 ANALYSIS

This was a live project that I worked on during the COVID-19 pandemic, during which I had just begun learning Python. Although this project did not yield any significant insights, it was my first live project where I compiled my own dataset from various sources.

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MNIST Data

Through this project, I initiated a "Hello World" program for Deep Learning and developed an interest in these types of networks and began to further my education in this field.Check it out

Dogs vs Cats Image Classification-CNN

I used a Kaggle dataset to determine whether a given image is of a cat or a dog. Through this project, I learned about various techniques and tools such as Keras, preprocessing techniques, the PIL library, the train_test_split method, the Sequential model, Conv2D layers, MaxPool2D layers, Flatten layers, Dense layers, the relu activation function, and the sigmoid activation function. Check it out

Sepsis_Watch: A Machine Learning-Powered Monitoring System

Sepsis is a serious medical condition that requires early detection and prediction to improve patient outcomes. Machine learning can be used to analyze patient data and identify patterns to predict sepsis. A sepsis prediction project aims to develop a machine learning-based system to monitor patients and identify those at risk of developing sepsis. The goal is to improve patient outcomes and reduce sepsis-related deaths.

Major Learnings : How to think like a Data Scientist, Data Preprocessing, Data Cleaning, Data Visualization, Feature Engineering, Feature Selection, Model Building, Model Evaluation, Model Deployment, Model Monitoring, Model Maintenance

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Kitchen Assistant: A Recipe Scraping and Q&A Bot

This project aims to scrape recipe data from various websites and use the extracted information to answer various questions about the recipe that a user may have, such as "What are the ingredients?" or "What is the cooking time?". The project would likely involve the use of web scraping libraries such as BeautifulSoup or Scrapy, as well as natural language processing (NLP) techniques to understand the user's question and provide an appropriate answer.

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Skill Indexer : A Skills Scraping and Job Matching Tool

This project aims to scrape the skills listed on resumes and match them to job roles to identify how many skills a candidate has that are suitable for a particular job. The project would likely involve the use of web scraping libraries such as BeautifulSoup or Scrapy, as well as natural language processing (NLP) techniques such as bigram and trigram to extract the skills from resumes and match them to job roles.

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