日韩三级在线_国产精品3区_亚洲精品a_成人网页_国产成人精品久久_国产精品国产精品国产专区不片

        1、培訓過程中，如有部分內容理解不透或消化不好，可免費在以后培訓班中重聽；
        2、培訓結束后,授課老師留給學員聯系方式,保障培訓效果,免費提供課后技術支持。
        3、培訓合格學員可享受免費推薦就業機會。

Deep Learning vs Machine Learning vs Other Methods

When Deep Learning is suitable
Limits of Deep Learning
Comparing accuracy and cost of different methods
Methods Overview

Nets and Layers
Forward / Backward: the essential computations of layered compositional models.
Loss: the task to be learned is defined by the loss.
Solver: the solver coordinates model optimization.
Layer Catalogue: the layer is the fundamental unit of modeling and computation
Convolution?
Methods and models

Backprop, modular models
Logsum module
RBF Net
MAP/MLE loss
Parameter Space Transforms
Convolutional Module
Gradient-Based Learning
Energy for inference,
Objective for learning
PCA; NLL:
Latent Variable Models
Probabilistic LVM
Loss Function
Detection with Fast R-CNN
Sequences with LSTMs and Vision + Language with LRCN
Pixelwise prediction with FCNs
Framework design and future
Tools

Caffe
Tensorflow
R
Matlab
Others...