Anup T
The star rating is calculated by averaging the reviews provided by all clients the talent has worked with for a significant amount of time.
If such data is not available, the star rating is calculated from the fraction of work sessions approved by their past clients versus the total tracked by the talent.
If such data is not available, the star rating defaults to the interview rating of the talent at the time of the vetting process.
Other data including reviews from interviews are available on the talents’ profiles.
If such data is not available, the star rating is calculated from the fraction of work sessions approved by their past clients versus the total tracked by the talent.
If such data is not available, the star rating defaults to the interview rating of the talent at the time of the vetting process.
Other data including reviews from interviews are available on the talents’ profiles.
ML ENGINEER Preferred Title
$31.25 /hr $ 50.0K /yr Hourly Rate and Yearly Salary
Overview
Basic Summary
LD Talent History - Worksession Approval 99.0%
- Average Response Time 3.3 hours
- Average Count of Messages/Day 1.0
- Project Completion Rate 2/4
- Interview Acceptance Rate 4/6
- Timezone Overlap 28h PST, 28h UTC
- Earned Hours 34.00
- Code Quality 60%
- Soft Skill Attributes 60%
- Expertise 2/3
- Coding Challenges 60%
- No. of Lifelong Learning Projects 2
- No. of Coding Challenges Completed 2 More details
- Desktop Windows
- Phone Android
- Member Since May 22, 2019
- Profile Last Updated Mar 09, 2022
- Last Activity April 28, 2022, 5:24 p.m. UTC
- Location India
Profile Summary
ML Engineer with Full Stack Development Experience. Skilled in Machine Learning, Deep Learning, Natural Language Processing, API development, Django, HTML, Web Scraping and Automation, Selenium, Python, Pandas, scikit-learn
Skills
Total Experience: 4 years
Python (5E, 4Y)
5 experiences, across 4 yearsMachine learning (4E, 4Y)
4 experiences, across 4 yearsPython Selenium (3E, 4Y)
3 experiences, across 4 yearsscikit-learn (1E, 4Y)
1 experience, across 4 yearsDjango (1E, 4Y)
1 experience, across 4 yearsPandas (1E, 4Y)
1 experience, across 4 yearsDeep learning (1E, 4Y)
1 experience, across 4 yearsFlask (2E, 1Y)
2 experiences, 1 yearData Engineering (1E, 1Y)
1 experience, 1 yearAzure (1E, 1Y)
1 experience, 1 yearVisual Studio (1E, 1Y)
1 experience, 1 yearData visualization (1E, 1Y)
1 experience, 1 yearJavaScript (1E, < 1Y)
1 experience, less than a yearMySQL (1E, < 1Y)
1 experience, less than a yearJupyter (1E, < 1Y)
1 experience, less than a yearData Science (1E, < 1Y)
1 experience, less than a year
Weekly Availability
Timezone Overlap with 06 - 21 per Week: 28h PST, 28h UTC
Day
Sunday
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
UTC
00 - 10
00 - 10
00 - 10
00 - 10
00 - 10
00 - 10
00 - 10
PST
17 - 03
17 - 03
17 - 03
17 - 03
17 - 03
17 - 03
17 - 03
Vetting
- Interview Data
- Agile Development Process
- Productivity and Responsiveness
- Teamwork
- Software Engineering
- Logical Thinking
- Technical Strength
- Intellectual Merit
- English Communication
- Documentation
- System Design
- Coding Challenges60%
- Algorithms Score60%
- General Score60%
- Easy Algorithm
- Correctness60%
- Performance60%
- Medium Algorithm
- Correctness60%
- Performance60%
- Hard Algorithm
- Correctness60%
- Performance60%
- Expertise2/3
- Design Patterns and Architectures2/3
- Debugging2/3
- Stack Traces2/3
- Testing2/3
- System Administration2/3
- Soft Skill Attributes60%
- Entrepreneurial60%
- Whole Brained60%
- Divergent Thinking / Creativity60%
- Design Ability60%
- Empathy60%
- Project Management Ability60%
- Security60%
- Code Quality60%
- Complex Logic60%
- Models60%
- Controllers60%
- Templates60%
- APIs60%
- Training/Testing Data Models60%
- Code Readability60%
- Ongoing Evaluation
- Number of Lifelong Learning Project2
- Number of Coding Challenge Completed3
Experience
Senior Consultant
Employment
Jan 2022 - Mar 2022
KPMG Company
Technology Industry
Project: Predicting errors in Invoice system
- Flask
- Python
- Data Science
- Machine learning
- Used Pycaret to automate the selection of best machine learning models
- Used Python modules such as pandas to process, clean and store data into databases
- Achieved a recall of 68% using the automated model selection techniques using Pycaret
- Applied data science principles to create a business case from the invoice audit data
- Used flask and azure VM services to deploy the model for real time predictions
ML Engineer
Employment
Jun 2021 - Feb 2022
KPMG Company
Energy Industry
Project: Development of RO location strategy for IOCL
- Data visualization
- Data Engineering
- Azure
- Machine learning
- Visual Studio
- Flask
- Python
- Used machine learning models such as XGBoost to predict 3 year sales forecast using historical and geospatial data for each of the 80k+ retail outlets (RO) in India
- Developed and deployed data fetching APIs from client systems using Flask
- Developed end to end ETL pipelines using Azure data factory to perform data engineering and Python to automate and schedule tasks
- Used databricks and Azure ML to automate and schedule ML Pipelines. Used Visual studio for source code management
- Deployed the model and created API to be consumed in Power BI dashboard for data visualization
Software Developer
Contract
Apr 2018 - Dec 2021
Power Exchange of India Ltd Company
Energy Industry
Project: RTM Decision Support System
- scikit-learn
- Pandas
- Machine learning
- Deep learning
- Python Selenium
- Django
- Python
- Developed a web application as a decision support system for clients using mentioned technologies
- Used Python Selenium to scrape publicly available data and used js charting library for visualization
- Used pandas for dataframe cleaning, manipulation and transformations
- Used Machine learning techniques from scikit-learn module such as Random Forest regressor and deep learning techniques such as LSTMs to predict the daily demand for states
- Used Django to build APIs for deployment
Data Science Consultant
Passion Project
Nov 2020 - Feb 2021
LD Talent Company
Energy Industry
Project: RTM IEX Price Forecasting using Bagging & Boosting Ensembles
- Python Selenium
- Jupyter
- Python
- Machine learning
- Used Python to develop the Machine learning project
- Used Python selenium to extract daily power exchange prices from IEX India website
- Used Jupyter notebooks for development and experimentation of ML Models
- Used timeseries techniques such as ARIMA and machine learning techniques such as RandomForest and XGBoost to predict day ahead power prices on Indian Energy Exchange
LD Experience
Client Projects
Developer
Contract
May 2019 - Sep 2019
TruePartner Client's Company/Project
Arts and Entertainment Industry
- Python Selenium
- Python
- JavaScript
- MySQL
- Used Python Selenium and JavaScript DOM manipulation in conjunction with Beautiful soup to extract and automate data fetching from LinkedIn premium accounts.
- LinkedIn automation using selenium webdriver python
- Used Python for data processing and conversion to required formats
- Used MySql to store data into database
- Used flask to integrate with database for fetching the scraped results to user via JSON response payloads
Did a good job on building some scrapers.
Coding Challenges
Skill:
- Python
- Machine learning
- Python Selenium
- scikit-learn
- Django
- Pandas
- Deep learning
Basic
Sep 2020 - Jan 2022
Basic
Sep 2020 - Jan 2022
Basic
Sep 2020 - Jan 2022
Video Projects
How to implement django-tenant-schemas with a fixed URL
Sep 2020 - Jan 2022
Frontend Developer
Technology
- Python
- Machine learning
- Python Selenium
- scikit-learn
- Django
- Pandas
- Deep learning
- Led user research for a new construction site documentation tool.
- Hosted workshops to synthesize user insights into design requirements.
- Designed 3D concepts and built prototypes to investigate new tool form factors.
- Researched existing digital solutions and prioritized key features for app release.
LD Ventures
Thea
Sep 2020 - Jan 2022
Frontend Developer
Technology
- Python
- Machine learning
- Python Selenium
- scikit-learn
- Django
- Pandas
- Deep learning
- I used the Django Rest Framework to create a multi tenant API with the aid of the django-tenant-schemas package.
- I used the Postgres Database as the persistence layer and specifically the PostgreSQL Schemas to ensure that all tenants using the API had their data.
- I used the REST architecture in designing my API.
- Researched existing digital solutions and prioritized key features for app release.
Qualifications
Education
Birla Institute of Technology & Science
Aug 2011 - Jul 2015
Bachelors of Engineering with Honors (Civil Engineering)
International Institute of Information Technology
Sep 2020 - Sep 2021
PGD in Machine Learning & Artificial Intelligence (Machine Leaning & Artificial Intelligence)
Courses
Data Science: Natural Language Processing (NLP) in Python
Feb 2021 - Mar 2022
Udemy
- Pandas
- Data Engineering
- Machine learning
- Deep learning
- Data Science
- Natural language processing
- Python
Time Series Analysis in Python
Jul 2020 - Jan 2021
Udemy
- Data visualization
- Data Science
- Machine learning
Reviews
Client Project Reviews
TruePartner
Did a good job on building some scrapers.