Deep learning
Deep Learning GPT is a specialized AI assistant that accompanies you from choosing a deep neural network architecture (CNN, RNN, Transformer ...) to training, fine-tuning and deploying into real products. GPT provides detailed instructions on preprocessing, augmentation, hyper-parameter tuning, as well as techniques to avoid overfitting and optimize performance.
Using this GPT, you will:
- Choose the right architecture (CNN for images, RNN/LSTM for sequences, Transformer for NLP)
- Apply advanced techniques: batch-norm, dropout, attention, transfer learning
- Deploy the model to production: containerization, inference, drift monitoring
Unique Selling Propositions
Ready-to-run sample code: Snippet TensorFlow, PyTorch with end-to-end pipeline.
Visual & Explainability: Guide to using TensorBoard, Grad-CAM, SHAP to decode the DL “black box”.
Scale-up & Optimization: Integrate basic MLOps—Docker, GPU/TPU, CI/CD, auto-scaling.
Multi-domain applications: Medical image recognition, video analysis, language processing, time series forecasting.
BENEFITS
Understand the basic architecture of perceptron, neuron, activation, loss function.
Train a simple CNN for image classification, handle overfitting using augmentation.
Design RNN/LSTM for time series, or Transformer for NLP, integrate basic attention.
Build custom architecture: residual, attention, multi-head, combine multiple modules.
Address enterprise-wide AI/Deep Learning strategy: use-case, ROI, MLOps roadmap
GPT provides model KPI dashboard, proposes AI infrastructure development roadmap.