Upwork home
Sign up
Project Catalog
DesignDesign
Video & AudioVideo & Audio
Development & ITDevelopment & IT
MarketingMarketing
Writing & TranslationWriting & Translation
MoreMore

You will get your machine learning model app build as a flask python web framework

Ayorinde O.Status: Offline
Ayorinde O. Ayorinde O.
4.8
Preview imagePreview image

Let a pro handle the details

Buy Web Application Programming services from Ayorinde, priced and ready to go.
Ayorinde O.Status: Offline
Ayorinde O. Ayorinde O.
4.8
Preview imagePreview image

Let a pro handle the details

Buy Web Application Programming services from Ayorinde, priced and ready to go.

Project details

You will get a machine learning prediction web app built with Flask written in python.
-A machine learning modeling will be carried out to select the best-performed algorithm on the data.
-The trained machine learning model will be saved and created by pickle a python module. To serialize the files on disc
-The machine learning web framework will be created by flask
-The structuring of the web app will be done by HTML programming language
-Requirments txt file will be created
-Local Run and Test the app for deployment
- Monitoring and tracking of the machine learning development process with JIRA
Skills:
- Programming: Python
- Tools: Vscode
- Frameworks: TensorFlow, Keras, Pytorch
- Libraries: Scikit-Learn, Numpy, Pandas, NLTK, CNTK, Matplotlib, Dash (Plotly), SciPy
- Version control and Issue Tracking: GIT, JIRA
Programming Languages
HTML & CSS, Python
Coding Expertise
Performance Optimization, Design

What's included $250

These options are included with the project scope.

$250
  • Delivery Time 7 days
  • Number of Revisions Unlimited
    • Design Customization
    • Responsive Design
    • Source Code
4.8
3 reviews
67% Complete
(2)
33% Complete
(1)
1% Complete
(0)
1% Complete
(0)
1% Complete
(0)

CY

Charles Y.
5.00
May 18, 2023
Looking for academic editors for Mechanical Engineering

LT

Lee T.
4.40
Jul 24, 2022
Data analyst / ML engineer needed to predict an outcome. Ayo is trustworthy and competent in the realm of ML. However, we had trouble communicating over Zoom due to his poor internet connection. I ultimately only received one of the two deliverables I wanted. I'm unsure of whether this was due to communication problems or him accepting to take on a python matplotlib problem outside of his ML expertise. He assured me up front he could complete both tasks in a reasonable amount of time, but it did not work out that way.

I would recommend Ayo for ML problems.

LT

Lee T.
4.85
May 26, 2022
Data analyst / ML engineer needed to predict an outcome. Ayo is highly skilled. I provided him with an obfuscated data set and had him compete against two other ML contractors on the same project, which I already knew the solution to. His work was superior. While the other contractors failed to produce insights and claimed the data set had too much randomness, Ayo prevailed because of a better approach and the use of more powerful tools. In fact, his results were beyond what I understood, despite my deep understanding of the data. I did not expect an additional value add beyond what I'd already discovered on my own. I'll definitely be hiring him again.
Ayorinde O.Status: Offline

About Ayorinde

Ayorinde O.Status: Offline
MLOps & Machine Learning Engineer | End-to-End ML Systems
4.8  (3 reviews)
Johannesburg, South Africa - 8:12 pm local time
I am a Machine Learning & MLOps Engineer with strong experience designing, building, and deploying production-grade end-to-end ML systems — from data ingestion to scalable model serving and monitoring.

With a background in both academic research and industry projects, I bridge the gap between real-world deployment and research-grade machine learning

🔹 What I Do

I build complete ML systems — not just models.

✔ Data Engineering & Feature Pipelines
✔ Model Development (Regression, Classification, NLP, Deep Learning)
✔ LLMOps (RAG, Embeddings, Vector Databases, Prompt Engineering)
✔ MLflow Experiment Tracking
✔ Dockerized Model Deployment
✔ Kubernetes (Minikube → Amazon EKS)
✔ Real-Time Streaming with Kafka
✔ CI/CD with GitHub Actions & Azure DevOps
✔ Monitoring with Prometheus & Grafana
✔ Cloud Deployment (AWS Lambda, S3, Redshift)

Tools & Technologies

ML & AI:
Scikit-learn, TensorFlow, PyTorch, CNNs, NLP, Transformers, LLMs

LLMOps:
RAG, Vectorization, Embeddings, Prompt Engineering

MLOps:
MLflow, DVC, Docker, Kubernetes, Amazon EKS, GitHub Actions, Azure DevOps, Amazon Sagemaker

Data & Streaming:
Apache Kafka, Quix Streams, PostgreSQL, Amazon S3, Amazon Redshift

Monitoring:
Prometheus, Grafana, Drift Monitoring

Backend & APIs:
Flask, FastAPI, REST APIs

CI/CD:
GIthub Actions


🔹 Why Work With Me?

I design systems for production — not just notebooks

Strong cloud + DevOps integration

Real-time ML architecture experience

Research-backed ML modeling skills

Clean, modular, scalable code

Experience leading ML engineering projects

If you need:

A full MLOps pipeline built from scratch

Deployment of ML models to AWS or Kubernetes

Real-time ML systems

LLM-powered applications

Optimization of existing ML infrastructure

Let’s build something scalable and production-ready.

With a strong foundation in Python, JavaScript, and Linux, I leverage a wide range of tools and technologies, including CI/CD pipelines, Docker, Kubernetes, and cloud platforms such as AWS, Google Cloud, and Azure. My hands-on experience extends to frameworks like TensorFlow, Keras, and PyTorch, as well as MLOps tools such as MLflow, Airflow, and Evidently AI.

I have a proven track record in data engineering, visualization, and application development, using tools like Spark, SQL, BigQuery ML, Node.js, React.js, Flask, Streamlit, and Dash. My skill set also includes working with vector databases, embeddings, and large language models (LLMs), where I utilize platforms like LangChain, Ollama, and ONNX for generative AI applications.

Driven by a passion for innovation, I excel in collaborative environments that embrace agile methodologies, utilizing GitHub Actions, GitLab CI/CD, Jenkins, Jira, and VS Code for streamlined development. Whether deploying cloud-native applications or creating real-time dashboards with Grafana, my goal is to deliver impactful, scalable solutions.

I use Python, Javascript, Linux, CI/CD, Gitlab, Jenkins, AWS, Google Cloud, Streamlit, Dash, SQL, BigQuery ML, Node.js, React.js, Flask, Dockers, Spark, GitHub Actions, Azure, Tensor Flow, Keras, Cloud Devop, Vercel, MLflow, Databricks, Airflow, Generative AI, Ollama, LangChain, LLM, Airflow, Grafana, ONNX, Prefect, Hopsworks, Evidently Ai, Git Bash, Jira, Jupyter Notebook, VS Code, Linux, UNIX, MacOS, Pytest, Embeddings, Vector databases, Kubernetes, Iac.
Tools: Python, Jupyter, Pycaret, Data Studio, BigQuery,




Steps for completing your project

After purchasing the project, send requirements so Ayorinde can start the project.

Delivery time starts when Ayorinde receives requirements from you.

Ayorinde works on your project following the steps below.

Revisions may occur after the delivery date.

creating the environment and installing dependencies

I will describe how to set up the environment, and install all the dependencies.

Machine learning Modeling

Also, take you through the machine learning modeling.

Review the work, release payment, and leave feedback to Ayorinde.