Cotton Disease Classification Using Deep Learning
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Summary
Developed an end-to-end deep learning solution to accurately classify cotton plant diseases, demonstrating proficiency in CNN development and MLOps.
About
Detail-oriented and results-driven Data Scientist with hands-on experience in machine learning, statistical analysis, and data visualization. Proficient in Python, SQL, and TensorFlow, with a proven ability to develop predictive models and derive actionable business insights from complex datasets. Adept at collaborating in cross-functional teams to deploy end-to-end AI solutions, passionate about leveraging data to solve real-world problems and drive impactful outcomes.
Work
BIT Infotech
|Data Scientist
Vadodara, Gujarat, India
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Summary
Assisted in data science initiatives, developing predictive models and visualizations to deliver actionable insights for a technology and data solutions provider.
Highlights
Streamlined data collection, cleaning, and analysis processes, enhancing data quality and accessibility for critical modeling initiatives.
Collaborated effectively with cross-functional teams to develop and implement predictive models and data visualizations, supporting informed decision-making.
Utilized Python, R, and SQL to efficiently manipulate and analyze large datasets, extracting key features for machine learning applications.
Gained practical experience in applying various machine learning algorithms to address complex data challenges and derive valuable insights.
Contributed innovative ideas during brainstorming sessions, fostering a collaborative environment for problem-solving and solution development.
Education
Parul Institute of Engg. and Tech
Limda, Gujarat, India
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Bachelor of Technology (B.Tech)
Computer Science
Skills
Programming Languages
Python, SQL, R.
Machine Learning
Supervised Learning, Unsupervised Learning, Deep Learning, Convolutional Neural Networks (CNNs), Machine Learning Algorithms.
Libraries & Frameworks
TensorFlow, PyTorch, Scikit-Learn, Numpy, Pandas.
Data Visualization & Tools
Power BI, Microsoft Power BI, Gradio, Jupyter.
Data Analysis
Data Collection, Data Cleaning, Statistical Analysis, Data Manipulation.
AI/ML Development Lifecycle
Model Development, Model Deployment, Data Preprocessing, Model Robustness, Generalization.