You will get Machine learning model text classification
Project details
You will receive custom-built machine learning and deep learning models tailored to your business or research needs. With years of experience in developing and deploying AI solutions, I specialize in delivering high-performance models for prediction, classification, and data-driven decision-making. My services are not only technically sound but also practical, ensuring the solutions are easily applicable to your workflows. The work I deliver is of top quality, thoroughly tested, and designed to maximize accuracy and efficiency. Let me help you harness the power of AI to achieve your goals.
Machine Learning Tools
Azure Machine Learning, Keras, NumPy, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, TensorFlow, XGBoostWhat's included
| Service Tiers |
Starter
$100
|
Standard
$300
|
Advanced
$700
|
|---|---|---|---|
| Delivery Time | 3 days | 7 days | 14 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 1 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 1 | 3 | 2 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | ||
Source Code | - |
Optional add-ons
You can add these on the next page.
Additional Revision
+$50
Additional Scenario
(+ 2 Days)
+$50
Additional Graph/Chart
(+ 2 Days)
+$150Frequently asked questions
About Mohamed
Data Scientist , Machine Learning Models , Zapier
Alexandria, Egypt - 10:48 pm local time
Titanic Survival Prediction:
- Built a logistic regression model using Python libraries like NumPy, Pandas, and Scikit-learn to predict survival outcomes based on passenger data.
House Price Prediction:
- Developed a machine learning model with Python using Pandas, Scikit-learn, and Matplotlib to predict house prices based on features like location and size.
Image Classification:
- Implemented a convolutional neural network (CNN) using TensorFlow and Keras for classifying images into categories.
Text Classification:
Created a natural language processing (NLP) pipeline using Python with NLTK, Scikit-learn, and SpaCy to classify text into predefined categories.
Steps for completing your project
After purchasing the project, send requirements so Mohamed can start the project.
Delivery time starts when Mohamed receives requirements from you.
Mohamed works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Gathering
Review the provided dataset and project objectives to understand the client's requirements fully. Address any clarifications if needed.