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Prathamesh Khade

Profile

Prathamesh Khade is a dedicated data science and machine learning enthusiast, currently pursuing a minor in Data Science. He has completed internships at TE Connectivity and Tata Motors, focusing on demand forecasting and prototype planning, respectively. With a strong foundation in data preprocessing, feature engineering, and model evaluation, Prathamesh excels in developing and implementing machine learning algorithms to solve complex problems. He is passionate about exploring the latest advancements in machine learning and is eager to connect with fellow enthusiasts.

Skills

  • Languages: Python, SQL, R
  • Tools: Jupyter Notebook, Pycharm, VS Code
  • Data Science: Data Wrangling, EDA, ETL, Visualization
  • Machine Learning: Supervised & Unsupervised Learning, Deep Learning, Reinforcement Learning, Transfer Learning
  • Mathematics for ML: Statistics & Probability
  • Visualization Tools: Tableau, Power BI, Excel
  • Databases: MySQL, PostgreSQL

Projects

  1. Fashion product recommendation system:

    • Developed a fashion recommender system using computer vision and natural language processing.
    • Implemented feature extraction from images with a pre-trained ResNet50 model and Nearest Neighbors algorithm for similarity search.
    • Integrated a chatbot using Sentence Transformers for text-based recommendations.
    • Libraries used: Hugging Face, TensorFlow, OpenCV, Streamlit.

  2. Bank loan analysis using PowerBI and MySQL:

    • Created a bank loan analysis dashboard in Power BI, delivering interactive visualizations and key performance indicators for loan portfolios to stakeholders.
    • Tools used: MySQL, Excel, PowerBI.

  3. Demand forecasting:

    • Managed large datasets from diverse sources, conducted thorough cleaning and preprocessing before analysis.
    • Utilized statistical and machine learning techniques to construct predictive models, enabling accurate forecasting and informed decision-making.
    • Achieved a notable 5-10% increase in accuracy through refined methodologies and innovative approaches.
    • Libraries used: NumPy, Matplotlib, Dart, Pandas.

Work Experience

  • Research Intern at Tata Motors (Jun 2023 - Sep 2023):

    • Focused on prototype planning and manufacturing.
    • Developed an Automated Guided Vehicle (AGV) with a weight-carrying capacity of 200 kg.
    • Utilized CATIA for design and conducted simulations using the Roboteq AGV simulator.

  • Machine Learning Intern at TE Connectivity (Dec 2022 - May 2023):

    • Specialized in demand forecasting through machine learning.
    • Developed accurate and reliable forecasting models for predicting consumer demand.
    • Leveraged skills in data analysis, statistical modeling, and machine learning techniques.

Education

  • Bachelor of Technology - BTech, Data Science (Jun 2022 - Jun 2024)

    • Pimpri Chinchwad Education Trust's Pimpri Chinchwad College Of Engineering
    • Grade: 7.8

  • Bachelor of Technology - BTech, Mechanical Engineering (Jul 2020 - May 2024)

    • Pimpri Chinchwad Education Trust's Pimpri Chinchwad College Of Engineering
    • Grade: 8.03
    • Activities: Part of team Automatons (Robotic team) which ranked 3rd in Robocon 2021.

Certifications

  • Google Business Intelligence (Issued Mar 2024)
  • Natural Language Processing on Google Cloud (Issued Mar 2024)
  • Introduction to Artificial Intelligence (AI) by IBM (Issued Mar 2024)
  • Production Machine Learning Systems (Issued Feb 2024)
  • Advanced Recommender Systems by EIT Digital (Issued Feb 2024)
  • Recommendation Systems on Google Cloud (Issued Feb 2024)
  • Generative Deep Learning with TensorFlow (Issued Feb 2024)
  • Deep Learning by DeepLearning.AI (Issued Jan 2024)
  • Generative AI with Large Language Models by DeepLearning.AI (Issued Dec 2023)
  • Generative Adversarial Networks (GANs) by DeepLearning.AI (Issued Oct 2023)
  • Introduction to Embedded Machine Learning by Edge Impulse (Issued Oct 2023)
  • Introduction to Generative AI by Google Cloud Skills Boost (Issued Jul 2023)
  • Practical Time Series Analysis by The State University of New York (Issued Jul 2023)
  • Reinforcement Learning by University of Alberta (Issued Jun 2023)
  • Machine Learning for Supply Chains by LearnQuest (Issued May 2023)
  • Leverage Data Science for a More Agile Supply Chain by University of California, Irvine (Issued Apr 2023)
  • Python for Cybersecurity by Infosec (Issued Apr 2023)
  • Machine Learning by Stanford University (Issued Nov 2022)
  • Machine Learning for Trading by Google Cloud Community India (Issued Sep 2022)

Publications

  • SPEED AND DIRECTION CONTROL OF DC MOTOR BY USING ARDUINO
    • International Journal for Science and Advance Research In Technology · Aug 28, 2021
    • The system consists of Arduino board, L293D Motor driver, HC-06 Bluetooth module, LCD, Motor, Potentiometer, etc. This system is used to change the speed and direction of DC Motor. The direction control of DC Motor is done by H-bridge arrangement, and the speed is controlled by giving pulse width modulation signal.

Test Scores

  • GATE (Data Science & AI) 2024: Score: 32.67 · Feb 2024

Languages

  • Hindi