Data Science Modeling
Starting at
$
25
About this service
Summary
FAQs
What programming languages do you use for designing machine learning and deep learning projects?
I use Python and R, which are widely used programming languages for machine learning and data science, to design custom machine learning and deep learning pipelines.
Can you explain the process of designing a machine learning or deep learning project?
Certainly! The process typically involves data preprocessing, exploratory data analysis, feature engineering, model selection and training, model evaluation, and deployment in production environments.
Can you work with large datasets?
Yes, I have experience working with large datasets and can efficiently handle them in your projects.
Can you provide documentation and explanations?
Absolutely! I deliver most of my work as Jupyter notebooks, where I use clear English to write paragraphs as a caption for the Python or R code. Additionally, I can provide a video walkthrough of the solution if needed, where I go through the code and explain it.
Can you deploy machine learning models as APIs?
Yes, I use Fast/Flask, a Python framework, to deploy machine learning models as APIs to serve your website or mobile app.
Can you help me run the code?
Yes, I can help you set up your Python environment and run the code.
What's included
Codebase with Detailed Comments
A clean and well-organized repository (e.g., GitHub or GitLab) containing all the code used for data collection, preprocessing, modeling, and evaluation. The code will be commented thoroughly to explain the logic behind each step, from data loading and cleaning to model training and evaluation. It will also include instructions on how to run the code, set up the environment, and reproduce the results.
Comprehensive Project Report
A concise report summarizing the objective, data overview, preprocessing, model development, evaluation, challenges, and key conclusions.
Example projects
Duration
4 days
