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$20 USD / hour
Flag of INFlag of IN
ichalkaranji,
india
$20 USD / hour
It's currently 7:41 PM here
Joined June 12, 2021
1 Recommendation

Keshav S.

@keshavsarda503

annual-level-two.svg
4.9 (7 reviews)
4.9 (7 reviews)
3.6
3.6
$20 USD / hour
Flag of INFlag of IN
ichalkaranji,
india
$20 USD / hour
100%
Jobs Completed
85%
On Budget
88%
On Time
17%
Repeat Hire Rate

AIML | Data Engineer | Big Data | Cloud Computing

I am an experienced Data Scientist with skills in Data Analytics, Big Data, Cloud Computing, Python, Machine Learning, Artificial Intelligence. I have completed various courses and certifications on Big Data, Machine Learning and Cloud Technology as mentioned below - 1. AWS Certified Machine Learning - Specialty (March 2021) 2. Machine Learning Masters with Deployment, Ineuron (May 2021) 3. Data Science Foundation, Edureka (October 2020) 4. AWS Certified Developer - Associate (May 2021) 5. Google Certified Professional Cloud Architect (March 2021) 6. AWS Certified Solutions Architect - Associate (July 2020) 7. BigData - Ineuron (September 2020) I am excited to start at Freelancer. With my skills and expertise, I expect to deliver the best possible solutions.
Freelancer
Python Developers
India

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Portfolio Items

Created Python scripts for EDA, Data Cleaning, training ML models, and predictions.

Explored data, applied feature engineering techniques, trained models using Logistic Regression, Random Forest, and XGBoost. 3 separate training scripts for each of the models giving output model file, ROC curve, Feature Importance graph. Another prediction script uses output model/s and new unlabeled data to predict Classification probabilities.

Preprocessed by joining over the appropriate key column. Explored and cleaned by handling null and missing values. Applied PCA to reduce feature dimension. Trained 3 models with appropriate hyperparameters. Applied Inverse PCA transformation on prediction data before using model/s.

Working on creating a single file for providing data, input argument (customize), other requirements/resources to implement actions. Looking to create a pipeline on Cloud.

https://github.com/keshavs0305/scripting-training-and-prediction-tasks
Python Scripting : Train, Test and Predict with ML models
Created Python scripts for EDA, Data Cleaning, training ML models, and predictions.

Explored data, applied feature engineering techniques, trained models using Logistic Regression, Random Forest, and XGBoost. 3 separate training scripts for each of the models giving output model file, ROC curve, Feature Importance graph. Another prediction script uses output model/s and new unlabeled data to predict Classification probabilities.

Preprocessed by joining over the appropriate key column. Explored and cleaned by handling null and missing values. Applied PCA to reduce feature dimension. Trained 3 models with appropriate hyperparameters. Applied Inverse PCA transformation on prediction data before using model/s.

Working on creating a single file for providing data, input argument (customize), other requirements/resources to implement actions. Looking to create a pipeline on Cloud.

https://github.com/keshavs0305/scripting-training-and-prediction-tasks
Python Scripting : Train, Test and Predict with ML models
Created Python scripts for EDA, Data Cleaning, training ML models, and predictions.

Explored data, applied feature engineering techniques, trained models using Logistic Regression, Random Forest, and XGBoost. 3 separate training scripts for each of the models giving output model file, ROC curve, Feature Importance graph. Another prediction script uses output model/s and new unlabeled data to predict Classification probabilities.

Preprocessed by joining over the appropriate key column. Explored and cleaned by handling null and missing values. Applied PCA to reduce feature dimension. Trained 3 models with appropriate hyperparameters. Applied Inverse PCA transformation on prediction data before using model/s.

Working on creating a single file for providing data, input argument (customize), other requirements/resources to implement actions. Looking to create a pipeline on Cloud.

https://github.com/keshavs0305/scripting-training-and-prediction-tasks
Python Scripting : Train, Test and Predict with ML models
Created Python scripts for EDA, Data Cleaning, training ML models, and predictions.

Explored data, applied feature engineering techniques, trained models using Logistic Regression, Random Forest, and XGBoost. 3 separate training scripts for each of the models giving output model file, ROC curve, Feature Importance graph. Another prediction script uses output model/s and new unlabeled data to predict Classification probabilities.

Preprocessed by joining over the appropriate key column. Explored and cleaned by handling null and missing values. Applied PCA to reduce feature dimension. Trained 3 models with appropriate hyperparameters. Applied Inverse PCA transformation on prediction data before using model/s.

Working on creating a single file for providing data, input argument (customize), other requirements/resources to implement actions. Looking to create a pipeline on Cloud.

https://github.com/keshavs0305/scripting-training-and-prediction-tasks
Python Scripting : Train, Test and Predict with ML models
Created Python scripts for EDA, Data Cleaning, training ML models, and predictions.

Explored data, applied feature engineering techniques, trained models using Logistic Regression, Random Forest, and XGBoost. 3 separate training scripts for each of the models giving output model file, ROC curve, Feature Importance graph. Another prediction script uses output model/s and new unlabeled data to predict Classification probabilities.

Preprocessed by joining over the appropriate key column. Explored and cleaned by handling null and missing values. Applied PCA to reduce feature dimension. Trained 3 models with appropriate hyperparameters. Applied Inverse PCA transformation on prediction data before using model/s.

Working on creating a single file for providing data, input argument (customize), other requirements/resources to implement actions. Looking to create a pipeline on Cloud.

https://github.com/keshavs0305/scripting-training-and-prediction-tasks
Python Scripting : Train, Test and Predict with ML models
I have created a workflow for an automated Machine Learning System. It starts with taking new data, joining it with old data if available. Then it starts training with the required ML algorithm. After saving the trained model, it deploys that to an endpoint.

Workflow is triggered after a new data file comes to an S3 location. Step function state machine is where the rest of the process is done. The task of joining data is done by Lambda, which is responsible to join new data with old data if any. The Task of training is done next and Saving the trained model then. The last Task is done by Lambda by deploying the endpoint.
Automatic Model Training and Endpoint Deployment
Automatic Text Reading and Language Translation

Reviews

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Showing 1 - 5 out of 7 reviews
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4.4
[SEALED]
Did a good enough job, was on time
R
Flag of AU Rahul K. @rahk5616
5 days ago
5.0
$200.00 USD
I used Keshav for a machine learning job and he was a pleasure to work with. I certainly plan to use him again.
Python
Excel
Machine Learning (ML)
User Avatar
Flag of US Hal S. @halsegal
8 days ago
4.6
$30.00 USD
Keshav is very responsive!
Linux
MySQL
Database Administration
PostgreSQL
Google Cloud Platform
N
Flag of CO Nicolas U. @nicouribe9
14 days ago
5.0
$30.00 USD
Repeat work given to him, amazing quality on time and correct answer
Python
Machine Learning (ML)
Coding
Computer Science
P
Flag of TH Rin G. @pg0410
2 months ago
5.0
$300.00 AUD
Professional, on-time and on-budget. Keshav was a great help in developing a set of Python functions and Google cloud platform pipeline. Looking forward to working with him again.
Python
Google Cloud Platform
B
Flag of AU Bruce S. @BruceSem
3 months ago

Experience

Engineer Technology

Virtusa Consulting Services
Jul 2019 - Present
1. Researched 2-3 Quantum Algorithms with the perspective of implementing Machine Learning Algorithms. 2. Monitored and managed 900+ BigData Pipelines using Dataflow, Dataproc, BigQuery, Stackdriver, DataStudio. 3. Resolved 8000+ ServiceNow incidents achieving 99.98% SLAs. 4. Performed activities like Data and Memory Cleanup in a timely manner using AppEngine application ensuring uptime of VM Instances. 5. Responsibly communicated handovers during a shift change of 24x7 Managed Operations.

Research Consultant

WorldQuant
Jul 2018 - Jul 2019 (1 year)
1. Created more than 125+ market-neutral strategy alphas over a sharp ratio of 2.0 and achieved a weightage of 1% in a production environment. 2. Applied creative statistical techniques as a Data Engineering method to clean data and reduce the correlation of alpha. 3. Implemented ML algorithms to create complex and robust alphas.

Education

BS Physics

Indian Institute of Technology, Kanpur, India 2013 - 2018
(5 years)

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Top Skills

Python
5
Machine Learning (ML)
3
Google Cloud Platform
2
Coding
2
Quantum
1

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