Case Studies
Deep Authenticator
Revolutionizing Face Authentication with AI
Designed a cutting-edge Face Authentication System using advanced computer vision techniques. This state-of-the-art system detects faces and generates unique embeddings, providing secure, fast, and reliable face authentication across platforms.
Accuracy
98.6%
Response Time
1.5s/ auth
Deep Authenticator
Revolutionizing Face Authentication with AI
Designed a cutting-edge Face Authentication System using advanced computer vision techniques. This state-of-the-art system detects faces and generates unique embeddings, providing secure, fast, and reliable face authentication across platforms.
Accuracy
98.6%
Response Time
1.5s/ auth
Deep Authenticator
Revolutionizing Face Authentication with AI
Designed a cutting-edge Face Authentication System using advanced computer vision techniques. This state-of-the-art system detects faces and generates unique embeddings, providing secure, fast, and reliable face authentication across platforms.
Accuracy
98.6%
Response Time
1.5s/ auth
Named Entity Recognition (NER)
Unlocking Insights from Text Data with NER
Developed an efficient Named Entity Recognition (NER) model to extract key elements such as people, places, and monetary values from large datasets. This system improves data sorting and information retrieval for large-scale text analysis.
Extraction Accuracy
95%
Processing Speed
2.3s/ doc
Named Entity Recognition (NER)
Unlocking Insights from Text Data with NER
Developed an efficient Named Entity Recognition (NER) model to extract key elements such as people, places, and monetary values from large datasets. This system improves data sorting and information retrieval for large-scale text analysis.
Extraction Accuracy
95%
Processing Speed
2.3s/ doc
Named Entity Recognition (NER)
Unlocking Insights from Text Data with NER
Developed an efficient Named Entity Recognition (NER) model to extract key elements such as people, places, and monetary values from large datasets. This system improves data sorting and information retrieval for large-scale text analysis.
Extraction Accuracy
95%
Processing Speed
2.3s/ doc
US Visa Approval Prediction
Predicting US Visa Approvals with Machine Learning
Built a powerful machine learning model that predicts US visa approval chances. Implemented data analysis, model training, and hyperparameter tuning, then deployed the application on AWS EC2 with a full retraining pipeline.
Model Accuracy
89%
Processing Time
0.8s/ req
US Visa Approval Prediction
Predicting US Visa Approvals with Machine Learning
Built a powerful machine learning model that predicts US visa approval chances. Implemented data analysis, model training, and hyperparameter tuning, then deployed the application on AWS EC2 with a full retraining pipeline.
Model Accuracy
89%
Processing Time
0.8s/ req
US Visa Approval Prediction
Predicting US Visa Approvals with Machine Learning
Built a powerful machine learning model that predicts US visa approval chances. Implemented data analysis, model training, and hyperparameter tuning, then deployed the application on AWS EC2 with a full retraining pipeline.
Model Accuracy
89%
Processing Time
0.8s/ req
Automated ETL Pipeline for Financial Data Processing
Optimizing Financial Data with an Automated ETL Pipeline
Designed an automated ETL pipeline to ingest financial transaction data from multiple sources into Amazon Redshift using AWS Glue. The pipeline, built with Python for transformations, reduced processing time by 80% and automated daily reporting and trend analysis.
Data Processing Time Reduction
80%
Automation Level
100%
Automated ETL Pipeline for Financial Data Processing
Optimizing Financial Data with an Automated ETL Pipeline
Designed an automated ETL pipeline to ingest financial transaction data from multiple sources into Amazon Redshift using AWS Glue. The pipeline, built with Python for transformations, reduced processing time by 80% and automated daily reporting and trend analysis.
Data Processing Time Reduction
80%
Automation Level
100%
Automated ETL Pipeline for Financial Data Processing
Optimizing Financial Data with an Automated ETL Pipeline
Designed an automated ETL pipeline to ingest financial transaction data from multiple sources into Amazon Redshift using AWS Glue. The pipeline, built with Python for transformations, reduced processing time by 80% and automated daily reporting and trend analysis.
Data Processing Time Reduction
80%
Automation Level
100%
Data Engineer
Data Engineer
Data Engineer
Data Engineer
Data Engineer
and expert in
AI & Machine Learning
AI & Machine Learning
AI & Machine Learning
AI & Machine Learning
AI & Machine Learning
with over
3 years
3 years
3 years
3 years
3 years
of industry experience. Expertise extends in
building scalable
Data Pipelines
Data Pipelines
Data Pipelines
Data Pipelines
Data Pipelines
, Proficient in AWS & Azure
along with building end-to-end
data solutions impactfully.
Currently pursuing Masters in
Data Science
Data Science
Data Science
Data Science
Data Science
at SUNY Buffalo.
Data Engineer
Data Engineer
Data Engineer
Data Engineer
Data Engineer
and expert in
AI & Machine Learning
AI & Machine Learning
AI & Machine Learning
AI & Machine Learning
AI & Machine Learning
with over
3 years
3 years
3 years
3 years
3 years
of industry experience.
Expertise extends in
building scalable
Data Pipelines
Data Pipelines
Data Pipelines
Data Pipelines
Data Pipelines
Proficient in AWS & Azure
along with building end-to-end
data solutions impactfully.
Currently pursuing Masters in
Data Science
Data Science
Data Science
Data Science
Data Science
at SUNY Buffalo.
Data Engineer
Data Engineer
Data Engineer
Data Engineer
Data Engineer
and expert in
AI & Machine Learning
AI & Machine Learning
AI & Machine Learning
AI & Machine Learning
AI & Machine Learning
with over
3 years
3 years
3 years
3 years
3 years
of industry experience. Expertise extends in
building scalable
Data Pipelines
Data Pipelines
Data Pipelines
Data Pipelines
Data Pipelines
, Proficient in AWS & Azure
along with building end-to-end
data solutions impactfully.
Currently pursuing Masters in
Data Science
Data Science
Data Science
Data Science
Data Science
at SUNY Buffalo.
"He consistently exceeds our expectations"
"I recommend Dileep whole-heartedly"
"Loved to work with Dileep!"
"He consistently exceeds our expectations"
"I recommend Dileep whole-heartedly"
"Loved to work with Dileep!"
"He consistently exceeds our expectations"
"I recommend Dileep whole-heartedly"
"Loved to work with Dileep!"