You will get a Machine Learning Model with Deployment
Project details
You will get End to End Machine Learning Model for prediction/classification/clustering,
Data Driven Insights, Source Code and Unlimited Revisions still your satisfaction.
Model Build with Best Model or Your Custom Model and then Model deployment on Your GCP/Azure/AWS server (Cost for deployment is completely Your's) then 3 Days Follow-up and 1 Demo Live/Video.
Data Driven Insights, Source Code and Unlimited Revisions still your satisfaction.
Model Build with Best Model or Your Custom Model and then Model deployment on Your GCP/Azure/AWS server (Cost for deployment is completely Your's) then 3 Days Follow-up and 1 Demo Live/Video.
Machine Learning Tools
AnyLogic, Azure Machine Learning, ChatGPT, Deeplearning4j, Google Sheets, Keras, Microsoft Excel, Microsoft Power BI, NLTK, NumPy, NVIDIA AI Platform, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, SAS, scikit-learn, SciPy, SQL, Stanford CoreNLP, TensorFlow, TextBlob, XGBoostWhat's included
| Service Tiers |
Starter
$50
|
Standard
$70
|
Advanced
$100
|
|---|---|---|---|
| Delivery Time | 1 day | 2 days | 2 days |
Number of Revisions | 3 | 5 | Unlimited |
Number of Model Variations | 1 | 2 | 4 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code |
About Prathamesh
AI & Machine Learning | Artificial Intelligence, Cluster Analysis
Beed, India - 8:19 pm local time
Entry-level Data Scientist with strong skills in Python, Statistics, SQL, and Machine Learning.
Experienced in building end-to-end ML models, performing EDA, and deploying applications using
Flask and Streamlit. Passionate about solving real-world problems through data-driven
approaches and continuous learning.
Projects
1. Credit Card Default Prediction
* Built a Logistic Regression model to classify default payments. Achieved 85% accuracy after
hyperparameter tuning.
* Tools: Python, Pandas, Scikit-learn, Matplotlib
2. Walmart Sales Prediction
* Developed an XGBoost regression model (R²: 0.91) to predict weekly sales. Performed EDA to
analyze holiday and fuel price effects.
* Tools: Python, XGBoost, Pandas, Matplotlib
3. Resume Screening AI
* Created an ML-based system to score resumes using TF-IDF + Logistic Regression. Built a
Streamlit UI for real-time scoring.
Steps for completing your project
After purchasing the project, send requirements so Prathamesh can start the project.
Delivery time starts when Prathamesh receives requirements from you.
Prathamesh works on your project following the steps below.
Revisions may occur after the delivery date.
Problem Understanding and Data loading.
Data cleaning and preprocessing