The field of Data Science and Machine Learning is of particular interest to me as it combines both of, computers and critical problem-solving. Currently, I am still learning and understanding how all parts of data science come into play in the real world.
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▶️ Programming💻| Python
▶️ Frameworks and Libraries🖼| Pandas • Numpy • Matplotlib • Scikit-Learn • Keras
▶️ Data Analytics 💾 | MySQL • Microsoft Excel
▶️ Vizz 📈 | Tableau • Power BI
▶️ Web 🕸 | HTML • CSS
▶️ Tech Stack 👨💻| Git • VSCode • PyCharm • Sublime Text • Jupyter • Google Collab
▶️ Soft Skills 👬| Communication • Presentation • Flexibility
▶️ Work ethics 👷♂️| Figure out • Work hard and smart • Perfectionism
This is an NLP project which classifies news headlines into 40 topics using a BERT model wrapped into a Django app for user interaction. User can further save the input and the prediction to a local database using MySQL.
This project involves a Django app which detects guitar chords while live playing. This is still a work in progress.
Continuing the work of a previous Flask project, here I trained multiple models and included multiple features to get more accurate predictions. The models takes more number of features and gives a prediction.
In this project, I used a pretrained ResNet34 model to train the Fish Dataset on, which was taken from Kaggle. I achieved an accuracy of 99.70% within around 8 minutes.
Banking Customer Churn Rate is a project in which the model determines whether customers will leave the bank given certain information about them. I trained an XGBoost model on this customer dataset using cross-validation and hyper-tuned it to achieve an accuracy of 85.4% as compared to 81% and 75% on normal XGBoost model and Logistic Regression respectively.
This is a Flask api deployed on Heroku that uses Support Vector Machines with RBF to determine if someone will quit a job provided various information about that employee. I achieved an accuracy of around 77% during training for this model.
The project is a Machine Learning api, deployed on Heroku, which implements Logistic Regression to predict whether you would survive the Titanic disaster. The api is made with Flask using python. The project includes a model to predict the survival given three inputs.
This project involves manipulating dataset on Excel and creating Tableau dashboards for the same.
This project involves an analysis on World CO2 emissions from 1960 to 2011.
Here, I performed extensive data cleaning and data wrangling tasks using Pandas. Did Exploratory Data Analysis using Matplolib and Seaborn to create charts and analyze the data in a Jupyter Notebook.
This project involves an analysis using SQL and MS-Excel on Census data of India for the year 2011.
This project involves manipulating dataset on Excel and creating Tableau dashboards for the same.
This Excel file showcases a case study done on Google Sheets to give out incentives to different managers based on sales and giving out strategies for increasing the sales next month.
Skill verification certificate from HackerRank.
Certification for Deep Learning course using PyTorch framework with practical assignments and course projects.
Certification for an NLP course introducing to basic concepts of NLP with a Twitter hate speech detection project.
Certification for a course which introduces to Python libraries such as Pandas, Numpy, Matplotlib and ML libraries such as Scikit-learn.
Certification for understanding basic to intermediate concepts of the Python language.
Skill verification certificate from HackerRank.
Skill verification certificate from HackerRank.