Muhammad H
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Other data including reviews from interviews are available on the talents’ profiles but do not influence their star rating, though they do influence their position in the search results.
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 but do not influence their star rating, though they do influence their position in the search results.
Deep Learning and Computer Vision Engineer Preferred Title
$20.00 /hr $ 20.0K /yr Hourly Rate and Yearly Salary
Overview
Basic Summary
LD Talent History - Average Response Time 12.0 hours
- Average Count of Messages/Day 0.4
- Project Completion Rate 2/4
- Interview Acceptance Rate 4/6
- Timezone Overlap 37h PST, 66h UTC
- 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
- Software Engineering Process 3.0/5
- Technical Breadth 3.0/5
- Algorithmic Thinking 3.0/5
- Technical Strength 3.0/5
- Teamwork 4.0/5
- Intellectual Merit 4.0/5
- Desktop Windows
- Phone Android
- Member Since Apr 16, 2021
- Profile Last Updated Apr 25, 2021
- Last Activity Feb. 15, 2022, 3:27 a.m. UTC
- Location India
- Current Status Student
Profile Summary
Hi! I am Yusuf, an aspiring Machine Learning/Deep Learning Engineer, and Electrical Engineering student at IIT Gandhinagar.
Skills
Total Experience: 3 years
keras (4E, 2Y)
4 experiences, across 2 yearsComputer vision (5E, 2Y)
5 experiences, across 2 yearsDeep learning (4E, 2Y)
4 experiences, across 2 yearsFlutter (1E, 2Y)
1 experience, across 2 yearsJupyter (4E, < 1Y)
4 experiences, less than a yearPython (1E, < 1Y)
1 experience, less than a yearTensorflow (1E, < 1Y)
1 experience, less than a year
Weekly Availability
Timezone Overlap with 06 - 21 per Week: 37h PST, 66h UTC
Day
Sunday
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
UTC
04 - 18
10 - 18
10 - 18
10 - 18
10 - 18
10 - 19
04 - 19
PST
21 - 11
03 - 11
03 - 11
03 - 11
03 - 11
03 - 12
21 - 12
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
Software Engineer
Passion Project
Nov 2020 - Present
IIT Gandhinagar Company
Technology Industry
Project: An App for Fire Load Survey
- keras
- Computer vision
- Flutter
- Deep learning
- A Deep Learning based Computer Vision app to calculate the Calorific value per volume present in a room.
- Will be helpful in conducting Fire Safety Surveys in Civil Engineering applications for residential buildings.
- Trained the object detection model (SSD MobileNet) in Keras.
- Used Flutter to build the interface for the app.
Software Engineer
Passion Project
Mar 2021 - Mar 2021
Inter IIT Tech Meet 9.0 Company
Technology Industry
Project: Traffic Sign Recognition on GTSRB dataset
- Python
- Computer vision
- Tensorflow
- Jupyter
- Trained State of The Art Computer Vision models on the German Traffic Sign Recognition Benchmark (GTSRB).
- Used Tensorflow framework and Jupyter Notebooks to build and train the model, achieving an accuracy of 98.58%.
- Deployed it using the Streamlit library in Python.
- Interface allows user to extend the dataset by adding new classes and augmentations, then retrain the model, and evaluate on different metrics.
Software Engineer
Passion Project
Dec 2020 - Dec 2020
Passion Project Company
Technology Industry
Project: Image Super Resolution using DCGAN
- keras
- Computer vision
- Deep learning
- Jupyter
- Implemented a Deep Learning based Computer Vision algorithm that can super-resolve an image from 32x32 to 128x128.
- Used Keras framework and Jupyter Notebooks for building the model.
- Methodology used was Adversarial training using DCGANs.
Software Engineer
Passion Project
Dec 2020 - Dec 2020
Passion Project Company
Technology Industry
Project: Colorizing Grayscale Images
- keras
- Computer vision
- Deep learning
- Jupyter
- Implemented a Deep Learning based Computer Vision algorithm that can give a plausible colorization to grayscale images.
- Used Keras framework and Jupyter Notebooks for building the model.
- Implemented transfer learning on a pretrained ResNet50 model in an encoder-decoder architecture.
Software Engineer
Passion Project
Aug 2020 - Aug 2020
Passion Project Company
Technology Industry
Project: Mask Detector
- keras
- Computer vision
- Deep learning
- Jupyter
- Implemented a Deep Learning based Computer Vision algorithm that can give detect if a person is wearing a mask or not.
- Used Keras framework and Jupyter Notebooks for building the project.
- Used OpenCV and implemented the detection and classification model using a CNN.
Qualifications
Education
Indian Institute of Technology Gandhinagar
May 2019 - May 2023
B.Tech. (Electrical Engineering)
Courses
Machine Learning
May 2020 - May 2020
Coursera
- scikit-learn
- Matplotlib
- Artificial intelligence
- Machine learning
- MATLAB
Neural Networks and Deep Learning
Dec 2020 - Dec 2020
Coursera
- Computer vision
- Machine learning
- Deep learning
Artificial Intelligence
Jun 2020 - Jul 2020
Verzeo Edutech
- keras
- Artificial intelligence
- Machine learning
- Deep learning
- Computer vision