You will get a cleaned dataset, free from errors, inconsistencies, and missing values
Project details
You’ll get a clean, organized dataset ready for any kind of analysis or decision-making. I’m dedicated to making sure your data is as accurate and useful as possible. With over three years of hands-on experience in data science, I take pride in delivering high-quality work that sets a solid foundation for your projects. Whether it’s fixing missing values, removing duplicates, or handling complex transformations, I make sure every detail is handled with care. My goal is to make your data clean and reliable so you can focus on what really matters—making informed decisions.
Machine Learning Tools
NumPy, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, SQL, TensorFlow, XGBoostWhat's included
| Service Tiers |
Starter
$20
|
Standard
$50
|
Advanced
$100
|
|---|---|---|---|
| Delivery Time | 2 days | 3 days | 5 days |
Number of Revisions | Unlimited | Unlimited | Unlimited |
Model Validation/Testing | - | ||
Model Documentation | |||
Data Source Connectivity | - | - | |
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$10 - $40Frequently asked questions
About Gregory
Expert Software Developer and Data Scientist
Nairobi, Kenya - 10:25 pm local time
My comprehensive skill set includes:
* Programming Languages: Python, SQL
* Data Manipulation: Pandas, NumPy, Polars
* Machine Learning Libraries: Scikit-learn, TensorFlow, Keras, PyTorch, XGBoost, LightGBM
* Advanced Modeling Techniques: Polynomial Regression, Regularization (Lasso, Ridge), Gradient Boosting, Random Forests, Stacking, Blending, Ensemble Learning
* Data Visualization: Matplotlib, Seaborn, Plotly, Tableau, Power BI, D3.js
* Big Data Technologies: Hadoop, Spark, PySpark, Hive
* ETL Tools: Apache Airflow, Luigi, Talend
* Cloud Platforms: AWS, Google Cloud, Azure, Google BigQuery, AWS Redshift
* Model Deployment: Docker, Kubernetes, Flask, FastAPI, Streamlit, Heroku
* Natural Language Processing (NLP): NLTK, SpaCy, Hugging Face Transformers, Gensim, BERT, GPT
* Recommendation Systems: Surprise, Collaborative Filtering, Content-Based Filtering, Matrix Factorization
* Statistical Analysis: Regression (Linear, Logistic, Polynomial), Classification, Clustering, Time Series Analysis, Survival Analysis
* Feature Engineering: Feature Extraction, Feature Selection, Dimensionality Reduction (PCA, t-SNE), Data Augmentation
* Exploratory Data Analysis (EDA): Data Profiling, Pattern Discovery, Statistical Summary, Hypothesis Testing
* Data Storage and Management: MySQL, PostgreSQL, MongoDB, SQLite, Redis
* Data Integration: RESTful APIs, SOAP APIs, Web Scraping (BeautifulSoup, Scrapy)
* Version Control: Git, GitHub, GitLab
* Model Evaluation: Cross-Validation, Hyperparameter Tuning, ROC/AUC, Precision-Recall Curves, Confusion Matrix
* Technical Documentation: Jupyter Notebooks, Markdown, LaTeX, Sphinx
Steps for completing your project
After purchasing the project, send requirements so Gregory can start the project.
Delivery time starts when Gregory receives requirements from you.
Gregory works on your project following the steps below.
Revisions may occur after the delivery date.
Data Assessment and Initial Cleaning
I will review the dataset to identify missing values, duplicates, and inconsistencies, and perform initial data cleaning using Python, leveraging libraries such as Pandas, NumPy, and Scikit-learn for any preliminary data transformations.