Aniket
Verified
Contact this Expert
3+ Years
System Analyst, Data Analyst
Claim Genius
Industry: IT & Software, Logistics
Specialization: Anomaly Detection, Computer Vision, Natural Language Processing
India
$-
Tech Stack: Python, GitHub, Pandas, NumPy
Expert’s cases:
Applied Variance Inflation Factor (VIF) to discern multicollinearity and refine feature selection, enhancing the robustness of predictive models
Showcased prowess in Artificial Intelligence by creating a Convolutional Neural Network (CNN) model for precise image classification, demonstrating proficiency in cutting-edge computer vision techniques
Leveraged Natural Language Processing (NLP) for text classification, deftly extracting insights from textual data and contributing to comprehensive data-driven solutions
Integrated Power BI to craft dynamic dashboards, unveiling interactive data visualizations and driving informed decision-making
Implemented hyperparameter tuning techniques to optimize model configurations, significantly elevating accuracy and ensuring peak performance
Leveraged Git Hub and MLOps for streamlined model version control and seamless integration of machine learning pipelines, ensuring efficient collaboration and deployment
Commanded Time Series Analysis to predict and forecast trends, applying data-driven insights to anticipate future patterns and facilitate proactive decision-making
Employed Linux proficiency to execute data science tasks, fostering a versatile and efficient working environment
Diverted 32% of zonal load of Armstrong sorter by extending zone-8 conveyor in two different parts which helps in reducing connecting time
Reduced 5% of breakdown of sorters and profilers by daily analyzing data and with effective maintenance
Reduced 17.85 % of no power complaints from FY-2019 to Fy-2022 by effectively analyzing data
Total 34.6% no power complaints reduced in FY-2020 compared to FY-2019 on 22 kv Old kasheli feeder
Capitalized total 5.76 crore amount in FY-2022 for LT (low tension) maintenance with proper execution of plans after analyzing past records
Achieved zonal target of 7% reduction in NPC (no power complaints) for both FY 21 and 22