Unleash Deep Learning: Begin Visually with Caffe and DIGITS
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Unleash Deep Learning: Begin Visually with Caffe and DIGITS

An introduction to Deep Learning tools using Caffe and DIGITS where you get to create your own Deep Learning Model
4.5 (42 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
2,883 students enrolled
Created by Razvan Pistolea
Last updated 9/2016
Current price: $10 Original price: $150 Discount: 93% off
5 hours left at this price!
30-Day Money-Back Guarantee
  • 1 hour on-demand video
  • 1 Article
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Begin Deep Learning with a visual training method to increase ease and understanding
  • Create an LMDB database from the MNIST handwritten digits
  • Design a DNN with different layers like convolutions and pooling (subsampling)
  • Train a Deep Neural Network on CUDA enabled GPU
  • Deploy and Classify unseen test images
  • Evaluate the performance (top 1 and top 5) accuracy and confusion matrix of your model
View Curriculum
  • Ubuntu 14.04 or higher
  • install DIGITS deep learning framework (Caffe is included)

Learn the basics of Deep Learning with hands on exercises using the Caffe deep learning framework and the DIGITS visual interface. Build your own model and start classifying images.

Begin with a visual understanding of machine learning and deep learning concepts with this quick dive tutorial for beginners.

  • image classification
  • feedfoward neural network
  • convolutional neural network
  • digit recognition

A hot new topic with lots of opportunities

Artificial intelligence, machine learning and deep learning are in the news and all around us.  They give us the promise of computers solving tasks that until recently were very hard for computers: speech recognition, translation, object recognition, image classification, autonomous driving cars. 

Caffe framework is free, open sourced, continuously improved, has good documentation and even has an entire zoo of pre trained deep neural network models for image classification and other computer vision tasks. It is very fast and extensible and has most layers and utilities one could hope for (convolutions, pooling, relu, softmax, accuracy) so all you have to do is understand how to control this powerful tool.

DIGITS is NVIDIA's tool to help improve the process of designing, debugging and visualizing the inner workings of a deep neural network and works perfectly with Caffe.

The underling idea is very simple: instead of explicitly programming one should give lots of labeled examples and allow the computer to learn.

Content and Overview 

Suitable for beginning deep learning engineers. 

Thanks to DIGITS and Caffe there is a little programming and a lot of visual steps but a good mathematical and programming background is recommended.

You should already have Ubuntu (recommended) and DIGITS installed (a fork of Caffe will be included with the DIGITS installation).

The course will take you through the natural steps of getting training and testing data, designing a model, training the model and evaluating it.

Students completing the course will have the knowledge and courage to experiment and create amazing, useful and functional Convolutional Deep Learning Networks.

Who is the target audience?
  • SHOULD: students that want to begin Deep Learning with concepts and tools
  • SHOULD: students who want to learn and gain insights into why Deep Neural Networks are such a powerful and unique tool
  • SHOULD NOT: experts in Deep Learning
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Curriculum For This Course
13 Lectures
Introduction and Overview
1 Lecture 01:39

toy deep learning network

generalize to bigger real life problems

graphical interface called DIIGITS

Preview 01:39

Basic Machine Learning
2 questions
App 1: Your first Deep Neural Network
7 Lectures 35:18


download mnist, uncompress, read labels

Overview and Download MNIST

Deep Learning GPU Training System (DIGITS) by NVIDIA

Lightning Memory-Mapped Database (LMDB) 

supervized vs unsupervized learning

training vs validation vs testing

web server, jobs

25% for validation

over fitting

class imbalance

Preview 06:35


pooling, sub sampling

full connection, inner product

automatic check reader

generalize the lesson to real problem


gradient of the error, stochastic gradient descent

base learning rate



Preview 05:39

job directory

watch nvidia-smi

loss graph

accuracy graph

Step 4: Train Lenet

classify unseen handwritten digits

single, multiple images

confusion matrix

top-1 accuracy

top-5 accuracy

top N predictions per category

Step 5: Classify using the trained Lenet model

channels, height, width




feature maps

Preview 08:42

App 2: A simple custom DNN
3 Lectures 18:31

ipython notebook


fully connected feedforward neural network


bottom top

number of outputs

confusion matrix

Customize Lenet based on the simple ANN course

solver mode: GPU

solver type: SGC


mean file



caffe log output

iteration number

variable learn rate

Preview 07:16

2 Lectures 08:03

DIGITS archive


channels == 1


Deploy a trained model without using the DIGITS interface

Machine Learning Series

Part 1: Unleash Machine Learning: Build Artificial Neuron in Python

Part 2: Unleash Deep Learning: Begin Visually using Caffe and DIGITS (this course)

Part 3: Coming soon

Preview 00:07
About the Instructor
Razvan Pistolea
4.2 Average rating
234 Reviews
8,335 Students
4 Courses
Source Code Painter

I am a Machine Learning Engineer, Deep Learning Engineer and even an Indie Game Developer with a Major in Compilers and a Master's degree in Artificial Intelligence from University Politehnica of Bucharest.

I am passionate about Games and Artificial Intelligence. I love to give life to A.I. agents in my project or my friend's projects and I want to teach you too.