PRASHANT LANGARE

ML Developer

Honeywell

Pune

04.2019 - Current

Oversee and maintain core Machine Learning Concepts ,NLP,Deep Learning and modeling
Ensure user satisfaction and retention by providing responsive support Perform live demos to customers and nurture client relationships
Exploratory Data Analysis, Feature Scaling and Extraction, Feature Selection, Ensemble Techniques, Outlier Detection, Outlier Handling, Imbalance Data, Data Distribution, Missing Values, Imputation Technique, Data Sanity, Model Building, Model Evaluation, and Deployment are all things we work with.
PROJECT DETAILS:
Anticipate credit card default using the customer's current status and prior history.
The client is seeking for potential customers who will probably forget to use their credit card to make their next month's payment.
The client wants to target clients who could hurt their business
The Prospective customers who are most likely to forget to make their next credit card payment are sought after by the client
To complete this project, we utilized SKLEARN, Matplotlib, Seaborn, ML Algorithms, Outlier Handling, Feature Engineering, Feature Selection Technique, Ensemble Techniques, etc. Utilizing the proper machine learning techniques to produce personalized data models
By using supervised ML classification model which helped to find potential defaulters very easily and saved 30% of time
Blood Brain Barrier
Drug development for peripheral nervous system is hampered by the fact that only about 2% medicines cross the membrane
Only around 2% of medicines pass the membrane, which limits the production of several novel compounds, which the development of new drug for peripheral nervous system
Developed model that successful predicts drug penetration using machine learning and deep learning algorithms that minimum uses manual labor cost and processing unit
We used RDKIT, Neural Networks, AUC-ROC Curve, SKLEARN, Matplotlib,SMILES,Seaborn, ML Algorithms, Outlier Handling, Feature Engineering, Feature Selection Technique, Ensemble approaches, etc. for this project. We also trained classifiers and assembled classifiers. Filed reports, gathered information, and performed research
Proportion of the company's growth that is driven by organic growth as opposed to growth via advertising.
An insurance business that has previously provided insurance to its clients now need help creating a model to ascertain from prior data if the policyholder (client) will also be interested in the company's automotive insurance.
This insurance measure provides insight into two distinct areas
The first is the degree to which your current customers are pleased with your goods and services
Revenue per Policyholder is that measures the amount of revenue generated by the insurance company, per policyholder serviced
Proved successful working within tight deadlines and fast-paced atmosphere.
Exceeded goals through effective task prioritization and great work ethic.
Learned new skills and applied to daily tasks to improve efficiency and productivity.

Summary

Overview

Work History

ML Developer

Education

MBA -

Skills

Work Availability

Timeline

ML Developer

MBA -

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