Cutting-edge techniques in Deep learning
- Consistent Deep Learning Development Flow, using Widely used frameworks such as MXNet, PyTorch, TensorFlow
- Deep learning inference minimize latency and maximize throughput for applications
- Feasibility, Study and develop algorithmics, performance evaluation, training and validating
- MLP, CNN, RNN, FFNN… Neural Networks.
- Design and develop customized solutions using a variety of data to make Predictions (classification, localisation, control…)
- Image, Video, Time-series, Sensor-based signals (Motion, Driving, Flight), any devices collecting rich data.
