Build Neural Networks In Seconds Using Deep Learning Studio

Build Neural Networks In Seconds Using Deep Learning Studio, available at $19.99, has an average rating of 3.35, with 44 lectures, based on 181 reviews, and has 568 subscribers.

You will learn about 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. This course is ideal for individuals who are Anyone Curios About Data Science. or Anyone Interested In Python, Keras Or Tensorflow. or Anyone Who Does NOT Want To Learn Python But Would Like To Develop Machine Learning Models. or Anyone Wanting To Launch Their Data Science Career Faster. or Experienced Python Programmers Who Want To Know How To Develop Keras / Tensorflow Deep Learning Models Faster, Better, And Easier. or Anyone Interested In Deep Learning Studio. It is particularly useful for Anyone Curios About Data Science. or Anyone Interested In Python, Keras Or Tensorflow. or Anyone Who Does NOT Want To Learn Python But Would Like To Develop Machine Learning Models. or Anyone Wanting To Launch Their Data Science Career Faster. or Experienced Python Programmers Who Want To Know How To Develop Keras / Tensorflow Deep Learning Models Faster, Better, And Easier. or Anyone Interested In Deep Learning Studio.

Enroll now: Build Neural Networks In Seconds Using Deep Learning Studio

Summary

Title: Build Neural Networks In Seconds Using Deep Learning Studio

Price: $19.99

Average Rating: 3.35

Number of Lectures: 44

Number of Published Lectures: 43

Number of Curriculum Items: 44

Number of Published Curriculum Objects: 43

Original Price: 89.99

Quality Status: approved

Status: Live

What You Will 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.

Who Should Attend

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.

Target Audiences

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.

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!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Roadmap To Success

Lecture 3: Get Deep Learning Studio From Deep Cognition

Lecture 4: Loading A Prebuilt Handwriting Recognition Model

Lecture 5: Build An Advanced Deep Neural Network In Seconds

Lecture 6: Section 1 Conclusion

Chapter 2: Datasets For Machine Learning In Deep Learning Studio

Lecture 1: Introduction To Datasets In Deep Learning Studio

Lecture 2: Data And Datasets In Machine Learning

Lecture 3: Data Collecting Basics For Datasets

Lecture 4: Preloaded Datasets In Deep Learning Studio

Lecture 5: Uploading Your Own Dataset In Deep Learning Studio

Lecture 6: Configuring A Dataset In Deep Learning Studio For Training A Neural Network

Lecture 7: Section 2 Conclusion

Chapter 3: Building A Neural Network Model In Deep Learning Studio

Lecture 1: Introduction To Building A Neural Network Model In Deep Learning Studio

Lecture 2: The Model Canvas

Lecture 3: The Input Component

Lecture 4: Flatten Component

Lecture 5: Dense Layer Component – The Neural Network Layer

Lecture 6: AI Theory: From Human Neurons To Artificial Deep Neural Networks

Lecture 7: Batch Normalization Component

Lecture 8: Dropout Component

Lecture 9: The Output Component

Lecture 10: Putting It All Together And Building A Deep Neural Network With Hidden Layers

Lecture 11: Section 3 Conclusion

Chapter 4: Training A Neural Network In Deep Learning Studio

Lecture 1: Introduction To Training The Neural Network In Deep Learning Studio

Lecture 2: Batch Size And Epochs Explained

Lecture 3: HyperParameters Settings

Lecture 4: Running The Model Training Session

Lecture 5: Verifying The Model Training Results

Lecture 6: Section 4 Conclusion

Chapter 5: Deploying Trained Neural Network Models From Deep Learning Studio

Lecture 1: Introduction To Deploying Neural Network Models From Deep Learning Studio

Lecture 2: Inference

Lecture 3: Deployment Of Trained Model As Service

Lecture 4: Downloading Your Trained Neural Network Model As A Python File

Lecture 5: Section 5 Conclusion

Chapter 6: Improving And Optimising A Trained Model

Lecture 1: Introduction To Improving And Optimising A Trained Model

Lecture 2: Overfitting And Underfitting In Machine Learning

Lecture 3: Samples, Features, Model Size And Other Factors That Can Affect Results

Lecture 4: Section 6 Conclusion

Chapter 7: Course Conclusion

Lecture 1: What We Have Learned And Can Now Do

Lecture 2: Continuing Our Learning Process From Here

Lecture 3: TensorFlow Playground

Lecture 4: Bonus Lecture: Viewing Our Keras / Tensorflow Model in Jupyter Labs Interface

Instructors

Michael Kroeker
Technologist and Data Scientist

Rating Distribution

1 stars: 8 votes

2 stars: 14 votes

3 stars: 30 votes

4 stars: 57 votes

5 stars: 72 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!