You will get machine learning and deep learning models built in Python
Project details
I turn raw data into working models and clear insights. Whether you need a classic ML model or a deep neural network, I deliver a structured, readable Python solution you can actually run.
5+ years in Data Science. I cover the full path: data preparation, exploratory analysis (EDA), modeling, evaluation and clear conclusions.
What I do:
• Data cleaning and preprocessing
• EDA and visualization
• Classic ML: regression, classification, clustering, time-series forecasting
• Deep learning and neural networks: CNNs for images and sequence models (TensorFlow / Keras / PyTorch)
• Model evaluation, tuning and cross-validation
• Interpretable results and recommendations
Stack: Python, Pandas, NumPy, Scikit-learn, TensorFlow/Keras, PyTorch, Matplotlib/Seaborn, SQL.
You get a documented, ready-to-run notebook or script, the trained model with evaluation metrics, clear visualizations and an honest, business-oriented summary of findings.
5+ years in Data Science. I cover the full path: data preparation, exploratory analysis (EDA), modeling, evaluation and clear conclusions.
What I do:
• Data cleaning and preprocessing
• EDA and visualization
• Classic ML: regression, classification, clustering, time-series forecasting
• Deep learning and neural networks: CNNs for images and sequence models (TensorFlow / Keras / PyTorch)
• Model evaluation, tuning and cross-validation
• Interpretable results and recommendations
Stack: Python, Pandas, NumPy, Scikit-learn, TensorFlow/Keras, PyTorch, Matplotlib/Seaborn, SQL.
You get a documented, ready-to-run notebook or script, the trained model with evaluation metrics, clear visualizations and an honest, business-oriented summary of findings.
Machine Learning Tools
Keras, NumPy, pandas, Python, PyTorch, scikit-learn, TensorFlow, XGBoostWhat's included
| Service Tiers |
Starter
$60
|
Standard
$150
|
Advanced
$350
|
|---|---|---|---|
| Delivery Time | 2 days | 4 days | 7 days |
Number of Revisions | 1 | 2 | Unlimited |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 3 | 5 |
Number of Graphs/Charts | 3 | 6 | 10 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code |
Frequently asked questions
About Ruslan
Senior Data Science/ ML Engineer
Tbilisi, Georgia - 10:14 am local time
Machine Learning studio. I help companies turn raw, messy data into production-ready
models and decisions that move real business metrics.
My work covers the full DS/ML lifecycle: exploratory data analysis, ETL and data
pipelines, feature engineering, model training and deployment, ML system design, and
rigorous A/B testing. I work primarily in Python (pandas, scikit-learn, TensorFlow,
Keras, SQL, Docker), and I care as much about clean, reproducible code as I do about
model accuracy.
I also teach what I build. Through SENATOROVAI I run a hands-on ML program built on a
reverse-engineering method: start from working models, break down the math behind them,
then rebuild the algorithms from first principles. Understanding a system end to end is
exactly what I bring to every client project.
My work is public — 140+ open-source repositories on GitHub (@SENATOROVAI), where my
methods and standards are open to inspection. If you need someone to own a data problem
from the first raw file to a deployed model, and explain every decision along the way,
let's talk.
Steps for completing your project
After purchasing the project, send requirements so Ruslan can start the project.
Delivery time starts when Ruslan receives requirements from you.
Ruslan works on your project following the steps below.
Revisions may occur after the delivery date.
Data prep & EDA
I clean and explore your data and confirm the modeling goal and metrics.
Modeling & evaluation
I train and tune the model or neural network, then validate it with proper metrics.