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Hi I'm Bhavya Sheth,working as Senior Research Analyst @Media.net

My technical skills:

Analysis Tools: Python (Pandas, Numpy, Scikit-learn, Seaborn, Matplotlib, Plotly)

Programming: Python, SQL

Data Visualization: PowerBI

Databases: MySQL

SEO: On-page SEO, Off-page SEO, Technical SEO

Please reach out to me at [email protected]

Bhavya Sheth's Projects

data-analyst-with-python-track-datacamp- icon data-analyst-with-python-track-datacamp-

In this track, you’ll learn how to import, clean, manipulate, and visualize data—all integral skills for any aspiring data professional or researcher. Through interactive exercises, you’ll get hands-on with some of the most popular Python libraries, including pandas, NumPy, Matplotlib, and many more. You’ll also gain experience of working with real-world datasets, including data from the Titanic and from Twitter’s streaming API, to grow your data manipulation and exploratory data analysis skills, before moving on to learn the SQL skills you'll need to query data from databases and join tables. Start this track, grow your Python and SQL skills, and begin your journey to becoming a confident data analyst.

handwritten-digit-recognition-using-web-app icon handwritten-digit-recognition-using-web-app

This project trains a machine learning model to recognize digits using Tensorflow Library and then it creates a web based GUI to show the Predictions from that model the predictions will be in real-time

kpmg-virtual-internship icon kpmg-virtual-internship

In this online program, i got to complete similar work that our Graduates do at KPMG. I have learnt what it is like working at one of the world’s best data analytics team, and build skills required to excel as a analytics consultant.

ml-classification icon ml-classification

In this project the data is been used from UCI Machinery Repository. Main aim of this project is to predict telling tumor of each patient is Benign (class – 2) or Malignant (class – 4) the models used are – Decision tree Classification, Logistic Regression, K-Nearest Neighbors, SVM, Kernel SVM, Naïve-Bayes and Random Forest Classification.

streamlit-iris-dataset icon streamlit-iris-dataset

This is a web app for data science project. Where i have used Streamlit library for making a web app. Data used is the famous inbuilt dataset of iris flower with the help of machine learning model - Random forest Classifier, i have made a classification app

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