Learning notes for Lecture 7 Modeling sequences: A brief overview. by Geoffrey Hinton [1]
Category Archives: Deep Learning
Deep Learning 09: Small Tricks(2)
Let’s try some ways to speedup our learning!
Deep Learning 08: Small Tricks(1)
I was optimizing my code for the ConvNet these days. Not all the methods are doing good, because I do not have very strong knowledge on the hyper-parameters. Anyway, just write something I’ve learnt here.
TensorFlow 04 : Implement a LeNet-5-like NN to classify notMNIST Images
The blog is a solution of Udacity DL Assignment 4, using a CNN to classify notMNIST images. Visit here to get a full version of my codes.
Deep Learning 07: Are you talking to a machine?
Recently working on a shared task job of image annotation. An interesting paper saw on NIPS’15 was proposed by Baidu Research. Find paper here . Official website. This post is the study notes.
Deep Learning 06: R-CNN for Object Detection
This post is a learning notes from this paper: Rich feature hierarchies for accurate object detection and semantic segmentation
TensorFlow 03: MNIST and CNN
Tutorial please find here. https://www.tensorflow.org/versions/0.6.0/tutorials/mnist/pros/index.html
Deep Learning 05: Talk about Convolutional Neural Networks（CNN）
A multi-layer NN, able to process images and voice signals (2D), keep stability in rotations.
TensorFlow 02: Play with MNIST and Google DL Udacity Lectures
Something to say:
TensorFlow 01: multiple versions of numpy
Started to write another paper, also I am reading the DL Textbook, but still have time to try new things….the TensorFlow. Everything is in the website, but you are not along cuz errors are always be with you 😀
IreneLi 