You will get Transform Your Data with Fine-Tuned AI Models for NLP Tasks
Project details
The project focuses on spam detection using a transformer-based model. It involves collecting data using a custom dataset, followed by preprocessing and tokenizing the text. A suitable transformer model, such as BERT or RoBERTa, is fine-tuned on labeled data to classify as spam or non-spam. The model's performance is evaluated based on accuracy and other relevant metrics, and it is deployed for real-time detection if successful.
Machine Learning Tools
Azure Machine Learning, BERT, ChatGPT, GPT-3, Keras, NLTK, pandas, Python Scikit-Learn, PyTorch, scikit-learn, TensorFlowWhat's included
| Service Tiers |
Starter
$200
|
Standard
$250
|
Advanced
$300
|
|---|---|---|---|
| Delivery Time | 1 day | 2 days | 2 days |
Number of Revisions | 0 | 1 | 2 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | - | - | - |
Source Code |
About Mutahir
Machine Learning, Deep Learning & Computer Vision
Lahore, Pakistan - 1:33 pm local time
Able to do all the tasks related to computer vision and natural language processing.
I'm experienced in python.
Proficiency in both TensorFlow and PyTorch.
Some of the project are given below:
By using Machine Learning Algorithm (Linear Regression) , predicting the body measurement (waist)
Using Multiple Machine learning algorithms (Decision Tree, Random Forest, KNN & Logistic Regression ) on multiple datasets and comparing each other in terms of Accuracy, Inference time & Training time
Traffic Sign Classification
Facial Recognition
Steps for completing your project
After purchasing the project, send requirements so Mutahir can start the project.
Delivery time starts when Mutahir receives requirements from you.
Mutahir works on your project following the steps below.
Revisions may occur after the delivery date.
1: Data collection 2: Pre processing 3: Model selection and training