CDOSS Certificate

Deep Learning

Profiles that can prepare this certification contents: Data engineer, statistical engineer, Quantitative Methods engineer, Developer engineer, Applied Mathematics engineer and more.

Prerequisite: Data science level I

Plan of preparation

I deep feed-forward neural network

(a) Machine learning in the supervised context

(b) The formal neuron

(c) Neural networks

(d) Gradient descent algorithm

(e) Deep Learning: CPU, GPU and cluster

(f) Theano, Tensorflow and Keras

(g) Deep feed-forward neural network

II: Convolutional and recurrent neural network

1) Convolutional Neural Networks

(a) Convolution properties

(b) Convolution layers

(c) Consolidation (pooling)

2) Recurrent Neural Network (Recurrent Neural Networks)

(a) Prediction of time series

(b) LSTM Recurrent Neural Networks

(c) Short-term and long-term memory recurrent neural network for regression (LSTM Network For Regression)

(d) Short-term and long-term memory recurrent neural network using the window method (LSTM For Regression Using the Window Method)

(e) Short-term and long-term memory recurrent neural network with time steps (LSTM For Regression with Time Steps)

 

 

CDOSS Association

(Compliance for Data Open Source Software)

ūüďĆ Association CDOSS, ZI de Franchepr√©, Centre d’activit√©s Econoliques de Franchepr√©
54240 JOEUF (FRANCE)

‚úȬ† contact@cdoss.tech