You will get AI trained model for your custom Dataset
Project details
This project involves training AI models using Convolutional Neural Networks (CNNs) on a custom dataset to achieve up to 90% accuracy. The model can be implemented using MATLAB, PyTorch, or TensorFlow.
Dataset Preparation: Includes normalization, splitting, and data augmentation to ensure the data is well-suited for training.
CNN Architecture: Utilizes convolutional, pooling, and fully connected layers with ReLU activation and softmax or sigmoid for classification. Regularization techniques like dropout and batch normalization are applied to prevent overfitting.
Training Process: Optimization using algorithms such as SGD or Adam. Hyperparameters like learning rate, batch size, and epochs are tuned.
Evaluation Metrics: Accuracy, precision, recall, and loss are tracked throughout, ensuring model performance.
Frameworks: MATLAB is ideal for prototyping, PyTorch offers flexibility, and TensorFlow is suited for large-scale deployment.
Optimization: Fine-tuning, regularization, and learning rate scheduling are used to reach the target accuracy.
The project successfully achieves 90% accuracy with strong generalization capabilities.
Dataset Preparation: Includes normalization, splitting, and data augmentation to ensure the data is well-suited for training.
CNN Architecture: Utilizes convolutional, pooling, and fully connected layers with ReLU activation and softmax or sigmoid for classification. Regularization techniques like dropout and batch normalization are applied to prevent overfitting.
Training Process: Optimization using algorithms such as SGD or Adam. Hyperparameters like learning rate, batch size, and epochs are tuned.
Evaluation Metrics: Accuracy, precision, recall, and loss are tracked throughout, ensuring model performance.
Frameworks: MATLAB is ideal for prototyping, PyTorch offers flexibility, and TensorFlow is suited for large-scale deployment.
Optimization: Fine-tuning, regularization, and learning rate scheduling are used to reach the target accuracy.
The project successfully achieves 90% accuracy with strong generalization capabilities.
Machine Learning Tools
deeplearn.js, Google AutoML, GPT-3, Keras, MATLAB, MLflow, NumPy, OpenCV, pandas, Python, PyTorch, TensorFlowWhat's included
| Service Tiers |
Starter
$20
|
Standard
$100
|
Advanced
$200
|
|---|---|---|---|
| Delivery Time | 7 days | 7 days | 5 days |
Number of Revisions | 1 | 3 | Unlimited |
Number of Model Variations | 2 | 5 | 10 |
Number of Scenarios | 2 | 5 | 10 |
Number of Graphs/Charts | 2 | 5 | 8 |
Model Validation/Testing | |||
Model Documentation | - | - | |
Data Source Connectivity | - | - | |
Source Code | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$30 - $70
Additional Revision
+$10
Additional Model Variation
(+ 2 Days)
+$5
Model Documentation
(+ 2 Days)
+$20About Umar
CAD, 3d Design, FEA, CFD, Ansys, Matlab, ML, AI, Pytorch, Tensorflow
Rawalpindi, Pakistan - 7:13 pm local time
Solidworks: I am proficient in creating 3D models, assemblies, and drawings using Solidworks. I can also perform simulations and analyses to ensure the designs meet specific requirements.
Ansys: I am familiar with using Ansys for finite element analysis (FEA), computational fluid dynamics (CFD), and structural analysis. I can perform simulations and analyses to evaluate the performance of designs and make necessary adjustments.
Python: I have a strong foundation in Python programming and can help you with tasks such as data analysis, numerical computation, and automation.
Matlab: I have experience using Matlab for data analysis, numerical simulations, and programming. I can write scripts to perform complex calculations, visualize data, and automate tasks.
I am a detail-oriented individual who is committed to delivering high-quality work to my clients. I am always open to communication and feedback, and I will work with you to ensure that your project is completed to your satisfaction.
If you are in need of any of the services I offer, please do not hesitate to contact me. I am excited to work with you and help bring your projects to life!
Steps for completing your project
After purchasing the project, send requirements so Umar can start the project.
Delivery time starts when Umar receives requirements from you.
Umar works on your project following the steps below.
Revisions may occur after the delivery date.
Preprocessing or Converting Images to Grayscale
The images need to be preprocessed so that model can be Trained accurately on correct data
Design the Model
Changing the Convolutional layers to make the Ai model suitable to our needs