Nov 2022 – May 2023 · 6 mos

• Developed an Image Quality Indicator for satellite imagery, significantly enhancing vegetation detection capabilities by filtering out noisy images, thereby increasing overall model accuracy by 45%.
• Innovated tree health assessment techniques using satellite imagery based on Decision Trees and Random Forests, achieving an accuracy of 94%

Aug 2022 – Oct 2022 · 2 mos

Dec 2021 – Feb 2022 · 2 mos

Dec 2021 – Jan 2022 · 1 mo

• I worked as a data science intern at LetsGrowMore .
• I worked on 3 projects as a part of the internship . Below is the link for the description of my role and work .
• https://medium.com/@yaswanthi2001/my-experience-atlgmvip-as-a-data-science-intern-3b401eb94461
• My tasks
• 1)
• Level: Beginner level
• Project name: Iris Flowers Classification ML Project
• Description:
• In this project, I used the Iris flower dataset to create a supervised machine learning model to predict the class or type of a given flower. There were various numerical attributes present in the Iris dataset as the features. I used the multinomial logistic regression algorithm to train my data.
• 2)
• Level: Beginner level
• Project name: Music Recommendation
• Description:
• In this task, I had to predict the chances of a user listening to a song repetitively after the first observable listening event within a time window was triggered. If there are recurring listening events triggered within a month after the user’s very first observable listening event, its target is marked 1, and 0 otherwise in the training set.
• Basically, we had to predict whether a certain song was preferred and liked by the user or otherwise.
• We had to use extensive feature engineering due to the presence of several files as a part of the dataset with quite a few outliers and null values.
• We used the provided Kaggle dataset and achieved our goal by training a model according to our requirements.
• 3)
• Level: Beginner level
• Project name: Image to Pencil Sketch with Python
• Description:
• As a part of this task, I had to convert an uploaded image in the format of a .jpg or .png into its pencil sketch version. I resized the image, converted it into grayscale and smoothened the image to remove the noise and finally achieved the required results.
• I used Google colab as the IDE for all the above tasks and used Python as my programming language to accomplish the task.
• Git hub repository link :
• https://github.com/Yaswanthi01/LGMVIP-DataScience

Apr 2021 – Nov 2021 · 7 mos · California, United States

Oct 2020 – Feb 2021 · 4 mos

• I worked as an intern for web development in Python. We working based on
• the agile methodology in a product-based environment.
• Tools or software used:
• 1) Python
• 2) Sqlite3
• 3) Flask
• 4) HTML
• 5) CSS
• 6) Bootstrap
• 7) Concept of sessions
• 8) Gitlab / GitHub
• 9) Git commands