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Zhang T.

@zhang43

4.2
9
3.6
3.6
100%

AI | WEB DEVELOPER

$39 USD / Hour
・
Flag of
China (2:36 PM)
・
Joined on April 19, 2024
$39 USD / Hour
・
⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ SUCCESS in life is a matter not so much of talent and opportunity as of CONCENTRATION and PERSEVERANCE ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ Greetings! I am a senior software engineer with over 7 years of hands-on experience in developing robust, high-performance software applications. Throughout my career, I have successfully delivered numerous projects across various industries, ranging from startups to large enterprises. Key Skills: Programming Languages: Python, PHP, C/C++, JavaScript Frameworks & Technologies: Django, Flask, Laravel, .NET Core, React, Vue Database Management: SQL (MySQL, PostgreSQL, Oracle), NoSQL (MongoDB, Redis, Google Firestore) Cloud Platforms: AWS, Azure, Google Cloud Platform DevOps: Docker, Kubernetes, CI/CD pipelines (Jenkins, GitLab CI) Services I Offer: Full Stack Development: End-to-end development of scalable web applications. Backend Development: API development, microservices architecture. Frontend Development: Responsive UI/UX design, SPA development. Database Design: Efficient database schema design and optimization. System Architecture: Designing scalable and resilient systems. Why Hire Me: Expertise: Extensive experience in software architecture, design patterns, and best practices. Problem Solver: Strong analytical skills with a knack for solving complex problems. Quality Assurance: Committed to delivering high-quality, bug-free code. Collaboration: Effective communicator and team player, ensuring smooth project execution.
Verifications
On time
78%
On budget
78%
Accept rate
89%
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Portfolio

Portfolio

12140133
Project description. Analyzed motion sensor signals from human subjects in Time-domain and Frequency-domain to confirm their differentiability. Furthermore, a various statistical technique like t-SNE was employed to visualize how different motions of different subjects fall into the same cluster. XGBoost classifier was trained to predict the motion and even identify the specific subject with >95% accuracy with only using the small portion of the available data. The most useful sensors in general in terms of predicting specific motions and subject were gyrometers on arms and ankles.
AI engineer
Project description. Analyzed motion sensor signals from human subjects in Time-domain and Frequency-domain to confirm their differentiability. Furthermore, a various statistical technique like t-SNE was employed to visualize how different motions of different subjects fall into the same cluster. XGBoost classifier was trained to predict the motion and even identify the specific subject with >95% accuracy with only using the small portion of the available data. The most useful sensors in general in terms of predicting specific motions and subject were gyrometers on arms and ankles.
AI engineer
12140129
Project description. Constructed regression model using XGBooster regressor that can estimate the burning area from the future forest fire. In order to deal with the highly imbalanced target variable, the oversampling approach was taken to help the model to be sensitive to a small chance of forest fire occurrence. With the corresponding feature selection process, the model could achieve the RMSE of ~3.2.
AI engineer
Project description. Constructed regression model using XGBooster regressor that can estimate the burning area from the future forest fire. In order to deal with the highly imbalanced target variable, the oversampling approach was taken to help the model to be sensitive to a small chance of forest fire occurrence. With the corresponding feature selection process, the model could achieve the RMSE of ~3.2.
AI engineer
12140125
Project description. Designed a customized CNN model and implemented a transfer learning on VGG16 that achieved ~ 80% accuracy in classifying 7 different skin cancer types. While the target variables were highly imbalanced, the final model constructed was shown to well differentiate different classes solely based on their morphology. Intermediate layers of CNN were also visualized for deeper understanding of the system. The best model/weights have been saved.
Machine learning engineer
Project description. Designed a customized CNN model and implemented a transfer learning on VGG16 that achieved ~ 80% accuracy in classifying 7 different skin cancer types. While the target variables were highly imbalanced, the final model constructed was shown to well differentiate different classes solely based on their morphology. Intermediate layers of CNN were also visualized for deeper understanding of the system. The best model/weights have been saved.
Machine learning engineer
12140116
Project description. Built a customized CNN model with ResNET50-like residual blocks. Trained it with a small image set that was prepared from Google using google-images-download module. After searching for the optimized hyperparameters, the final model could achieve ~ 90% accuracy on a test set and the model was eventually applied to predict the happiness of my puppy, Lucky. Many of the mislabeled images were turned out to be very difficult even for me to classify as happy or sad.
CV Engineer
Project description. Built a customized CNN model with ResNET50-like residual blocks. Trained it with a small image set that was prepared from Google using google-images-download module. After searching for the optimized hyperparameters, the final model could achieve ~ 90% accuracy on a test set and the model was eventually applied to predict the happiness of my puppy, Lucky. Many of the mislabeled images were turned out to be very difficult even for me to classify as happy or sad.
CV Engineer
12140111
Project description. Deployed computer-vision-based business intelligence tool (KnowYourMove) that analyzes time-specific store traffics from store surveillance camera systems. By tracking the motion of individual customers over time (based on Single Shot Detector and centroid tracking algorithm), KnowYourMove generates information maps that can provide business owners with hidden insights to understand their customers better (in terms of their shopping routes and aggregated time spent in different areas). KnowYourMove has been deployed as a web application (currently hosted on AWS t2.micro
AI Engineer
12140054
Project description. The consulting group highlights their unique approach, differentiating themselves from traditional sales consulting firms. They focus on innovation, forward-thinking, and leveraging technology for human performance enhancement.
Michigan Manchester
12140133
Project description. Analyzed motion sensor signals from human subjects in Time-domain and Frequency-domain to confirm their differentiability. Furthermore, a various statistical technique like t-SNE was employed to visualize how different motions of different subjects fall into the same cluster. XGBoost classifier was trained to predict the motion and even identify the specific subject with >95% accuracy with only using the small portion of the available data. The most useful sensors in general in terms of predicting specific motions and subject were gyrometers on arms and ankles.
AI engineer
Project description. Analyzed motion sensor signals from human subjects in Time-domain and Frequency-domain to confirm their differentiability. Furthermore, a various statistical technique like t-SNE was employed to visualize how different motions of different subjects fall into the same cluster. XGBoost classifier was trained to predict the motion and even identify the specific subject with >95% accuracy with only using the small portion of the available data. The most useful sensors in general in terms of predicting specific motions and subject were gyrometers on arms and ankles.
AI engineer
12140129
Project description. Constructed regression model using XGBooster regressor that can estimate the burning area from the future forest fire. In order to deal with the highly imbalanced target variable, the oversampling approach was taken to help the model to be sensitive to a small chance of forest fire occurrence. With the corresponding feature selection process, the model could achieve the RMSE of ~3.2.
AI engineer
Project description. Constructed regression model using XGBooster regressor that can estimate the burning area from the future forest fire. In order to deal with the highly imbalanced target variable, the oversampling approach was taken to help the model to be sensitive to a small chance of forest fire occurrence. With the corresponding feature selection process, the model could achieve the RMSE of ~3.2.
AI engineer
12140125
Project description. Designed a customized CNN model and implemented a transfer learning on VGG16 that achieved ~ 80% accuracy in classifying 7 different skin cancer types. While the target variables were highly imbalanced, the final model constructed was shown to well differentiate different classes solely based on their morphology. Intermediate layers of CNN were also visualized for deeper understanding of the system. The best model/weights have been saved.
Machine learning engineer
Project description. Designed a customized CNN model and implemented a transfer learning on VGG16 that achieved ~ 80% accuracy in classifying 7 different skin cancer types. While the target variables were highly imbalanced, the final model constructed was shown to well differentiate different classes solely based on their morphology. Intermediate layers of CNN were also visualized for deeper understanding of the system. The best model/weights have been saved.
Machine learning engineer
12140116
Project description. Built a customized CNN model with ResNET50-like residual blocks. Trained it with a small image set that was prepared from Google using google-images-download module. After searching for the optimized hyperparameters, the final model could achieve ~ 90% accuracy on a test set and the model was eventually applied to predict the happiness of my puppy, Lucky. Many of the mislabeled images were turned out to be very difficult even for me to classify as happy or sad.
CV Engineer
Project description. Built a customized CNN model with ResNET50-like residual blocks. Trained it with a small image set that was prepared from Google using google-images-download module. After searching for the optimized hyperparameters, the final model could achieve ~ 90% accuracy on a test set and the model was eventually applied to predict the happiness of my puppy, Lucky. Many of the mislabeled images were turned out to be very difficult even for me to classify as happy or sad.
CV Engineer
12140111
Project description. Deployed computer-vision-based business intelligence tool (KnowYourMove) that analyzes time-specific store traffics from store surveillance camera systems. By tracking the motion of individual customers over time (based on Single Shot Detector and centroid tracking algorithm), KnowYourMove generates information maps that can provide business owners with hidden insights to understand their customers better (in terms of their shopping routes and aggregated time spent in different areas). KnowYourMove has been deployed as a web application (currently hosted on AWS t2.micro
AI Engineer
12140054
Project description. The consulting group highlights their unique approach, differentiating themselves from traditional sales consulting firms. They focus on innovation, forward-thinking, and leveraging technology for human performance enhancement.
Michigan Manchester
Changes saved
4.2 · 9 Reviews
Reviews
T
Project 38603568 has been deleted • $140 USD
The AI lip sync video exceeded my expectations, demonstrating impressive quality and accuracy. The developer was highly communicative and completed the project on time, showcasing strong expertise in AI and video production. I’m very satisfied with the overall experience and would gladly recommend their services to others.
Closed User
@teodora50
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Flag of
,
•
4 months ago
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Project for Zhang T. • €100 EUR
Ce freelance est vraiment professionnel , elle comprends très vite le besoin client
Hassan E.
@zakouzakou59280
•
Flag of
ARMENTIERES, France
•
5 months ago
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md file x.com icon in my github readme (5 stars ) • $10 USD
Zhang T. took all care of me and fast I was very happy as he got me a good source and tried it and worked better than expected Really hope Zhang T. will work with me in the future and recommend him to EVERYONE
Erich B.
@ejbest2000
•
Flag of
New York City, United States
•
5 months ago
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S
High Availability GPU Inference API using Kubernetes • $140 USD
I made a mistake, released payment before project start, I simply wanted to focus on other urgent issues. My observation is: after payment, Zhang is not available for planned work-session, and told me he has family issues and asked me to postpone work-session to his availability, which I did, but again not showing up, not responding to further freelancer communication now. My fault, I should not release all payment before project starts, I put my trust in hand of wrong person, hope others wont.
Wei S.
@shawei3000
•
Flag of
STIRLING, United States
•
5 months ago
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K
React Material UI Grid System Fix • $20 CAD
Great communication and like to work with him again.
Karies C.
@Karies923
•
Flag of
Richmond, Canada
•
5 months ago
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Experience
Backend Developer
Aug, 2022 - May, 2024
•
1 year, 9 months
Hopper
Aug, 2022 - May, 2024
•
1 year, 9 months
Engineered high-performance RESTful APIs with Node.js and Express, elevating flight booking experiences. Crafted robust data processing pipelines utilizing Kafka and Spark, boosting real-time flight data analytics. Developed scalable microservices architecture leveraging Docker and Kubernetes. Fortified API security and ensured GDPR compliance using OAuth 2.0 authentication protocols. Orchestrated CI/CD workflows with Jenkins and AWS, streamlining automated deployment processes.
Aug, 2022 - May, 2024
•
1 year, 9 months
Backend Developer
Jul, 2019 - Nov, 2021
•
2 years, 3 months
Tyk Technologies
Jul, 2019 - Nov, 2021
•
2 years, 3 months
Tyk Technologies is a company specializing in API management and service orchestration solutions. Expertly developed and maintained high-performance RESTful APIs leveraging Node.js and Go. Skillfully managed API lifecycle with Tyk API Gateway for enhanced security and control. Optimized MySQL and MongoDB database operations, designing efficient schemas for scalability. Implemented secure authentication and authorization protocols using OAuth 2.0 and JWT.
Jul, 2019 - Nov, 2021
•
2 years, 3 months
Frontend Developer
Sep, 2018 - Aug, 2019
•
11 months, 1 day
Outliant
Sep, 2018 - Aug, 2019
•
11 months, 1 day
Spearheaded frontend development at Outliant, a global, fully remote company specializing in design, development, and digital marketing services. Championed User Experience ՄUXՅ and User Interface ՄUIՅ design, ensuring intuitive and aesthetically pleasing interfaces. Directed the discovery phase for medium to large-scale projects, delivering comprehensive high-level design strategies.
Sep, 2018 - Aug, 2019
•
11 months, 1 day
Education
Tsinghua University
2015 - 2019
•
4 years
Bachelor's degree
Flag of
China
2015 - 2019
•
4 years
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