Hi, I'am PATIL AMIT
I am a data scientist with a passion for story telling.
I believe that words and data are the two most powerful
tools to change the world. & My skills include Data Scrap,
Collection,Analysis, visualization, ML, DL, NLP, PowerBi.
Download CV
About
Hi I'am PATIL AMIT
Basically i'm from Bhalki dist Bidar, Karnataka but currently staying in Hyderabad, Telangana, I have 9 Months of Experience as a Data Science Inern, I am Proficient in Python,ML,DL,NLP,HTML,CSS,Power Bi
1. I have developed a strong acumen for problem solving.
2. I enjoy an occasional challenge.
3. I often work on end-to-end data science projects that usually begin from collecting data from third party sources like kaggle,DrivenData,Zindi,Bitgrit..etc
4. End with delivering business insight in the form of customer segments.
5. I also enjoy going on sites like HackerRank and trying out their programming challenges
6. To enhence my skills so,i watched some of you tube channels like Campus-X, Krish naik and other..etc.
7. You can take a look at some of my projects and articles in the section below.
8. I will link my work to their GitHub repositories, so feel free to download my code and play around with it.
Qualifications
Bachelor of Engineering
Bheemanna Khandre Institute of Technology, Bhalki, Dist. Bidar, Karnataka
JUNE 2016 - JULY 2020 -6.72 cgpa
12th
Mahatma Gandhi Pu Science college Bhalki, Dist. Bidar, Karnataka
February 2015 - March 2016 -69.17%
10th
Shyamlal Memorial High School, Udgir, Dist Latur, Maharashtra
February 2013 - March 2014 -74.20%
Skills & Certifications
Professional Skills
All Skills are Based on My current Organisation i.e Data Science and Data Analytics
Python
80%
Machine Learning
85%
Deep Learning
75%
NLP
75%
MYSQL
75%
Power BI,Tableau
80%
FLASK , STREAMLIT
70%
Certifications
- Naresh IT Hyderabad
- Linkedin Learning
- TCS NQT
- TCS NQT
- IBM Cognitive Class
- IBM Cognitive Class
- IBM Cognitive Class
Work
DATA SCIENCE INTERN
Social Tek ai ml business solution, Hyderabad
- Oct 2021 - July 2022
Projects
1. Global Superstore Sales using Power BI
- Connecting Database with Power BI Desktop.
- Analyzing the tables and relations.
- Data Cleaning using Power Query Editor with
DAX (Data Analysis Expressions).and ultimately
- Developing an Interactive BI Dashboard / Report.
2. OLX House Rent Prediction
- Build the predictive model that gives the most estimated
Price based on the other features too.
- With the help of selenium and chromedriver I scrap the data.
- With the help of machine learning models got the r2_score of
0.71 & deploy this model using flask API and Heroku cloud.
Tools Used--> Selenium, Chromedriver, Numpy, Pandas, Matplotlib, Seaborn, Scipy, Scikit learns, Flask API
Deployment
3. flipkart clothes Recommendation System
- Recommended various types of Woman clothing.I Scrap the
data And,I've done data preprocessing .
- With the help of cosine similarity it will recommende the cloth
I got cosine similarity 0.85.
- Deploy this model using Streamlit and Heroku cloud.
Tools Used--> Selenium, Chromedriver, Numpy, Pandas,
NLTK, Sklearn.
Deployment
data And,I've done data preprocessing .
- With the help of cosine similarity it will recommende the cloth
I got cosine similarity 0.85.
- Deploy this model using Streamlit and Heroku cloud.
Tools Used--> Selenium, Chromedriver, Numpy, Pandas,
NLTK, Sklearn.
4. Movie Recommendation System
- The Goal of this Project is to Recommend a Movie which based on previous searched.
- I took the data from kaggle site..in that they give 2 DataSets i.e Credits and Movies
- I done all the things that related to Data Cleaning,and seperate
words, sentences.
- I fetch the pkl file and i deploy using streamlit & Heroku.
Tools Used --> Numpy, Pandas, Pickel,streamlit
Deployment
- I took the data from kaggle site..in that they give 2 DataSets i.e Credits and Movies
- I done all the things that related to Data Cleaning,and seperate words, sentences.
- I fetch the pkl file and i deploy using streamlit & Heroku.
Tools Used --> Numpy, Pandas, Pickel,streamlit
5. Object Detection Using RCNN And YOLO
- The goal of this project is to detect the different types of Obj & gives the best bboxes with labels.
- Help of pascal voc 2007 dataset. I did selective Search & IOU.
- Here the object is detected from a particular image & Give the bounding boxes with IOU score.
Tools Used --> Numpy, Pandas, Opencv, Tensorflow, Keras
- Help of pascal voc 2007 dataset. I did selective Search & IOU.
- Here the object is detected from a particular image & Give the bounding boxes with IOU score.
Tools Used --> Numpy, Pandas, Opencv, Tensorflow, Keras
6. Machine Translation Using Attensions
- Build a model that give translation of one to another language.
- I conclude that encoder-decoder along with attensions are more accurate
- I got the bleu score of 51.
Main keys:-RNN, LSTM,Encoder-Decoder,Attension-Mechanism
- I conclude that encoder-decoder along with attensions are more accurate
- I got the bleu score of 51.
Main keys:-RNN, LSTM,Encoder-Decoder,Attension-Mechanism
7. Hotel-Cancellation-Prediction
- The goal of this project is to find out the characteristic
of customers who cancelled Hotel booking.
- By doing an EDA And Building classification ML model to
predict cancellation.
- I used all machine Learning Algorithm In this I conclude that Random Forest Algorithm Is best for these Problem And Get r2_Score of 0.72 compare to other ML Algorithms
Tools Used --> Numpy, Pandas, Seaborn, Matplotlib, Sk-learn
of customers who cancelled Hotel booking.
- By doing an EDA And Building classification ML model to
predict cancellation.
- I used all machine Learning Algorithm In this I conclude that Random Forest Algorithm Is best for these Problem And Get r2_Score of 0.72 compare to other ML Algorithms
Tools Used --> Numpy, Pandas, Seaborn, Matplotlib, Sk-learn
8. What's App Chat Analysis
- The Goal of this Project is to Analysis the Chat That happend in Groups or One to One Person.
- Done the analysis things in that i done all statistical modeling.
Tools Used --> Regular Expression, Pandas, Pickle, Streamlit.
- Done the analysis things in that i done all statistical modeling.
Tools Used --> Regular Expression, Pandas, Pickle, Streamlit.