Document Classifier with Neural Network
Budget: €8 – €30 EUR
I need a neural network with one layer (perceptron) for classifying text documents. The main goal is to categorize these documents based on their topics, so prior experience with topic categorization is a plus.
Key Requirements:
- Design and implementation of a perceptron model for the neural network
- Training the model on a dataset of text documents to achieve topic categorization
- Ability to work with Python for the implementation
The project also involves comparing two training methods:
- Standard Gradient Descent (GD)
- Stochastic Gradient Descent (SGD)
Ideal Skills:
- Proficiency in neural network design and implementation, specifically with perceptron models
- Prior experience in text document classification and topic categorization
- Strong programming skills in Python
- Knowledge of training methods such as GD and SGD
I'm looking for a freelancer who can not only implement the neural network but also compare the effectiveness of the two training methods in achieving the specified topic categorization goal.
Key Requirements:
- Design and implementation of a perceptron model for the neural network
- Training the model on a dataset of text documents to achieve topic categorization
- Ability to work with Python for the implementation
The project also involves comparing two training methods:
- Standard Gradient Descent (GD)
- Stochastic Gradient Descent (SGD)
Ideal Skills:
- Proficiency in neural network design and implementation, specifically with perceptron models
- Prior experience in text document classification and topic categorization
- Strong programming skills in Python
- Knowledge of training methods such as GD and SGD
I'm looking for a freelancer who can not only implement the neural network but also compare the effectiveness of the two training methods in achieving the specified topic categorization goal.