You will get I will train and evaluate a machine learning model in Python
Project details
I bring real professional ML experience —
not just personal projects. I have worked
on a US-based Data Science team delivering
production ML solutions, and I write clean,
documented, reproducible code. You get a
working model, full evaluation report, and
code you can actually use.
not just personal projects. I have worked
on a US-based Data Science team delivering
production ML solutions, and I write clean,
documented, reproducible code. You get a
working model, full evaluation report, and
code you can actually use.
Machine Learning Tools
BERT, Deeplearning4j, GitHub Copilot, Keras, MLflow, NLTK, NumPy, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, SQL, TensorFlow, Word2vec, XGBoostWhat's included
| Service Tiers |
Starter
$50
|
Standard
$80
|
Advanced
$120
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 2 | 4 | 6 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code |
Frequently asked questions
About Fasih
ML Engineer | Python | PyTorch | TensorFlow | FastAPI | Flask
Gujranwala, Pakistan - 12:53 pm local time
with over a year of professional experience building
and shipping data-driven solutions.
I've worked as part of a US-based Data Science team
at Mavericks United where I built ML pipelines,
deployed models as REST APIs using FastAPI, and handled
large-scale data preprocessing in Python and SQL.
Before that I worked as an ML intern at IncaNet IT
Alliance in Lahore, training and evaluating models
for real client use cases.
On the project side, I recently delivered a live
courier service web platform for a real UK-based
courier company. It handles fare calculation,
bookings, and order tracking for businesses across
London and the UK built with Flask, Firebase,
and Google Cloud APIs.
My technical stack:
- Machine Learning: PyTorch, TensorFlow, Keras,
Scikit-learn
- NLP: BERT, Hugging Face Transformers
- Deployment: FastAPI, Flask, Docker
- Data: Pandas, NumPy, SQL, Web Scraping
- Cloud: Firebase, Google Cloud APIs
I work best on projects that go from raw data or
an idea all the way to something deployed and
working. I communicate clearly, hit deadlines,
and write clean documented code.
If you need an ML model trained, an API built,
data scraped and processed, or a full pipeline
deployed send me a message and let's talk
about your project.
Steps for completing your project
After purchasing the project, send requirements so Fasih can start the project.
Delivery time starts when Fasih receives requirements from you.
Fasih works on your project following the steps below.
Revisions may occur after the delivery date.
Review Requirements
Review your dataset and confirm problem type, target column and project goals
Data Preprocessing
Clean data, handle missing values, outliers and perform feature engineering