Build Neural Networks In Seconds Using Deep Learning Studio
3.9 (63 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
221 students enrolled

Build Neural Networks In Seconds Using Deep Learning Studio

Develop Keras / TensorFlow Deep Learning Models Using A GUI And Without Knowing Python Or Machine Learning
3.9 (63 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
221 students enrolled
Created by Michael Kroeker
Last updated 1/2019
English
English [Auto-generated]
Current price: $11.99 Original price: $89.99 Discount: 87% off
4 days left at this price!
30-Day Money-Back Guarantee
This course includes
  • 3 hours on-demand video
  • 6 articles
  • 4 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
Training 5 or more people?

Get your team access to Udemy's top 3,000+ courses anytime, anywhere.

Try Udemy for Business
What you'll learn
  • How To Build Deep Neural Networks In Seconds Using Deep Learning Studio.
  • Rapidly Build And Visualise Neural Networks Without Programming Skills.

  • How To Understand Neural Networks Without Math Formulas.

  • How To Build Neural Networks Without Programming.
  • How To Deploy Machine Learning Models Built Using Deep Learning Studio.
  • Understand Normalization Without Heavy Math Or Complicated Technical Explanations.
  • Understand Dropout Without Heavy Math Or Complicated Technical Explanations.
  • How To Download Neural Network Models Built In Deep Learning Studio As Python / Keras / TensorFlow Script.
  • Learn Practical Information On Developing Artificial Neural Networks, Data Collection, And Creating Robust Models.
Course content
Expand all 43 lectures 02:48:19
+ Introduction
6 lectures 26:25
Get Deep Learning Studio From Deep Cognition
06:18
Loading A Prebuilt Handwriting Recognition Model
07:05
Build An Advanced Deep Neural Network In Seconds
03:46
Section 1 Conclusion
00:08
+ Datasets For Machine Learning In Deep Learning Studio
7 lectures 32:05
Introduction To Datasets In Deep Learning Studio
01:02
Data And Datasets In Machine Learning
11:13
Data Collecting Basics For Datasets
10:58
Preloaded Datasets In Deep Learning Studio
02:00
Uploading Your Own Dataset In Deep Learning Studio
03:16
Configuring A Dataset In Deep Learning Studio For Training A Neural Network
03:22
Section 2 Conclusion
00:14
+ Building A Neural Network Model In Deep Learning Studio
11 lectures 29:11
Introduction To Building A Neural Network Model In Deep Learning Studio
01:57
The Model Canvas
01:40
The Input Component
00:53
Flatten Component
02:40
Dense Layer Component - The Neural Network Layer
03:55
AI Theory: From Human Neurons To Artificial Deep Neural Networks
04:34
Batch Normalization Component
05:35
Dropout Component
04:51
The Output Component
00:42
Putting It All Together And Building A Deep Neural Network With Hidden Layers
02:10
Section 3 Conclusion
00:14
+ Training A Neural Network In Deep Learning Studio
6 lectures 23:39
Introduction To Training The Neural Network In Deep Learning Studio
01:35
Batch Size And Epochs Explained
04:17
HyperParameters Settings
05:50
Running The Model Training Session
05:40
Verifying The Model Training Results
06:05
Section 4 Conclusion
00:12
+ Deploying Trained Neural Network Models From Deep Learning Studio
5 lectures 16:38
Introduction To Deploying Neural Network Models From Deep Learning Studio
02:27
Inference
07:55
Deployment Of Trained Model As Service
03:10
Downloading Your Trained Neural Network Model As A Python File
02:46
Section 5 Conclusion
00:20
+ Improving And Optimising A Trained Model
4 lectures 14:31
Introduction To Improving And Optimising A Trained Model
01:07
Overfitting And Underfitting In Machine Learning
03:25
Samples, Features, Model Size And Other Factors That Can Affect Results
08:57
+ Course Conclusion
4 lectures 25:47
What We Have Learned And Can Now Do
04:35
Continuing Our Learning Process From Here
00:07
TensorFlow Playground
11:38

In this Bonus Lecture we will be looking at how to use python programming code to look at our Deep Learning Studio tensorflow / keras model results. We will also learn the directory structure Deep Learning Studio uses to store the tensorflow / keras model and how to view, edit, and modify the python code of the machine learning models we build.

Bonus Lecture: Viewing Our Keras / Tensorflow Model in Jupyter Labs Interface
09:27
Requirements
  • Interest In Machine Learning And Neural Networks.
  • Interest Or Curiosity About Data Science.
Description

In this course you will Machine Learning And Neural Networks easily. We will develop Keras / TensorFlow Deep Learning Models using  GUI and without knowing Python or programming.

If you are a python programmer, in this course you will learn a much easier and faster way to develop and deploy Keras / TensorFlow machine learning models.

You will learn about important machine learning concepts such as datasets, test set splitting, deep neural networks, normailzation, dropout, artificial networks, neural network models, hyperparameters, WITHOUT hard and boring technical explanations or math formulas, or follow along code. Instead, you will learn these concepts from practical and easy to follow along teaching methods.

In this course, Deep Learning Studio will produce all the python code for you in the backend, and you never even have to even look at it (unless of course you want to). By the end of this course you will be able to build, train and deploy deep learning AI models without having to do any coding.

After taking this course you will be able to produce well written professional python code without even knowing what python is or how to program, Deep Learning Studio will do all this work for you. Instead you can easily stay focused on building amazing artificial intelligence machine learning solutions without programming.

Also, if you just want to learn more about Deep Learning Studio and get a jump start on this revolutionary ststem, this is the course for you! Deep Learning Studio is just beginning to shake up the data science world and how artificial intelligence solutions are developed!

Get ahead of the curve by taking this exciting and easy to follow along course!

Who this course is for:
  • Anyone Curios About Data Science.
  • Anyone Interested In Python, Keras Or Tensorflow.
  • Anyone Who Does NOT Want To Learn Python But Would Like To Develop Machine Learning Models.
  • Anyone Wanting To Launch Their Data Science Career Faster.
  • Experienced Python Programmers Who Want To Know How To Develop Keras / Tensorflow Deep Learning Models Faster, Better, And Easier.
  • Anyone Interested In Deep Learning Studio.