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I will do data science and ml in python
Data Science Web Development AI Engineer
Full Stack Developer & AI Engineer with expertise in Machine Learning, Deep Learning, NLP, and Computer Vision. I build scalable web apps and intelligent AI solutions using Python, React, Node.js, Ten...
About this Gig
About this Gig
Are you looking for a reliable and skilled data science expert who can help you with powerful insights and machine learning solutions in Python?
You're at the right place!
I specialize in Data Science, using Python to analyze, visualize, and model your data effectively. Whether you're working on a project, assignment, or need support with a business problem, I can provide clean, efficient, and professional solutions.
My services include:
- Data Cleaning & Preprocessing
- Exploratory Data Analysis (EDA)
- Data Visualization using Matplotlib, Seaborn, Plotly
- Machine Learning Models (Regression, Classification, Clustering, etc.)
- Model Evaluation and Tuning
- Working with Pandas, NumPy, Scikit-learn, and more
Why choose me?
Strong command of data science tools and libraries
Hands-on experience with ML algorithms
Clean, commented, and well-structured code
Fast delivery & professional communication
Lets bring your data to life with intelligent solutions. Feel free to contact me before placing the order!
Programming language:
Python
•
R
•
MATLAB
•
Colab
•
Java
Tools:
Jupyter Notebook
•
OpenCV
•
OpenNN
•
TensorFlow
•
Excel
•
MLflow
•
Colab
Technology:
Python
•
R
•
TensorFlow
•
Colab
•
MATLAB
•
Pandas
FAQ
What tools or libraries do you use for data science and ML?
I primarily use Python along with libraries such as Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, and sometimes TensorFlow or Keras, depending on your project requirements.
Can you help with academic assignments or student projects?
Yes! I can assist with student projects, assignments, and capstone tasks. All solutions will be well-commented and easy to understand.
Do you provide explanations along with the code?
Absolutely! I can provide detailed explanations, code walkthroughs, and if needed, a brief report about the steps followed in your data science or ML project.
