Deep Learning A-Z Hands-On Artificial Neural Networks

We have divided the tutorials into 2 volumes to represent the two main branches of the subject. Deep LearningSupervised Deep Learning Unsupervised Deep Learning. File Size: 3.1GB

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Deep Learning A-Z Hands-On Artificial Neural Networks

*** As seen on Kickstarter ***

Artificial Intelligence is increasing exponentially. It is clear that this is the case. The self-driving cars are logging millions of miles. IBM Watson is diagnosing patients more accurately than armies and Google Deepmind’s AlphaGo defeated the World champion in Go – a game in intuition plays a key part.

The more complex the AI problems, the better. Only Deep Learning It can solve complex problems, and that’s why it is at the heart of Artificial intelligence.

— Deep Learning A-Z? —

Here are five reasons to think this way Deep Learning A-Z™ really is different, and stands out from the crowd of other training programs out there:

1. ROBUST STUCTURE

Download it immediately Deep Learning A-Z Hands-On Artificial Neural Networks

Our first and most important focus was to give the course a solid structure. Deep Learning It is extremely complex and broad. To navigate it, you will need to have a clear and comprehensive view of it.

We have divided the tutorials into 2 volumes to represent the two main branches of the subject. Deep Learning: Supervised Deep Learning Unsupervised Deep Learning. We found this structure to be the most effective for mastering, with each volume focusing only on three different algorithms. Deep Learning.

2. TUTORIALS IN INTUITION

Many books and courses just give you the theory, math, and code. Many courses and books only focus on the theory, math, and coding. They forget to explain why you do what your doing. And that’s how this course is so different. We focus on developing an intuitive *feel* for the concepts behind Deep Learning algorithms.

Our intuition tutorials will ensure that you are able to understand the concepts on an intuitive level. You will also be able to see the benefits of coding by doing it yourself. This is a game-changer.

3. EXCITING PROJECTS

Are you fed up with courses that are based on outdated, over-used data?

Yes? You’re in for a surprise.

We will be using Real-World datasets in this class to solve Real-World business problems. This class is not about boring digit classification or boring iris datasets like we see in other courses. This course will help you solve six real-world problems.

Artificial Neural Networks How to solve Customer Churn problems
Convolutional Neural Networks Image Recognition
Recurrent Neural Networks To predict stock prices
Self-Organizing Maps for Investigating Fraud
Boltzmann Machines for creating a Recomender System
Stacked Autoencoders* to take on the challenge for the Netflix $1 Million prize

*Stacked Autoencoders is a brand new technique in Deep Learning These were not available a few years back. This method has not been explained in enough detail elsewhere.

4. CODING WITH HANDS

In Deep Learning A-Z™ we code together with you. Every tutorial starts with a blank sheet of paper and we create the code from scratch. This will allow you to understand how the code is assembled and what each line does.

We will also structure the code so you can download it and use it in your projects. We will also show you step-by-step how to modify the code to insert your data, and to customize the algorithm to suit your needs.

This course is an excellent way to build your career.

5. SUPPORT FOR IN-COURSE

Did you ever take a course, or read a book that you had questions about but couldn’t reach the author?

But this is a new course. This will be the most powerful and disruptive event in our history. Deep Learning The planet is a beautiful place. That responsibility comes with the obligation to be there for you when you need it.

Because we need to eat, and sleep, we have assembled a team professional Data Scientists to assist us. You will receive a reply within 48 hours if you ask us a question.

No matter how complex or difficult your query may be, we’ll help. Our goal is for you to succeed.

— The Tools

Pytorch, Tensorflow, and Pytorch have been the most popular open-source library. Deep Learning. Both will be covered in this course.

TensorFlow is a Google invention and is used by Google in their speech recognition system. It also powers the new Google Photos product, gmail and google search. Tensorflow is used by many companies, including AirBnb and Airbus, Ebay and Intel, Uber, and many others.

PyTorch, which is equally powerful, is being developed at Nvidia by leading universities such as Stanford, Oxford and ParisTech. PyTorch is used by companies such as Facebook, Saleforce, and Twitter.

Get your instant download Deep Learning A-Z Hands-On Artificial Neural Networks

Which is better? And for what purpose?

You will be able to compare the two and learn when Tensorflow is best and when PyTorch works best. We will compare them and offer tips and tricks on which one might work best under certain circumstances.

These libraries are only a year old. That’s the interesting part. This is what we mean when you say that this course will teach you the most cutting-edge techniques. Deep Learning Modèles and techniques

— Other Tools

Another open-source deep learning library is Theano. Although it is very similar in functionality to Tensorflow, we will still be covering it.

Keras is a wonderful library that you can implement Deep Learning models. It serves as a wrapper to Tensorflow and Theano. Keras allows us to create complex and powerful programs. Deep Learning You can create models using only a few lines. This library will enable you to see the whole picture of what you’re creating. This library will help you see everything clearly and organize it so you have a clear understanding and intuition of what you are creating.

— More Tools

Scikit-learn how to make the most of your Machine Learning library. We will use it mainly:

To evaluate the performance of our models using the most appropriate technique, kFold Cross Validation
Improve our models by Parameter Tuning
To preprocess our data so that our models can learn under the best conditions

We must mention the usual suspects. The entire course is built on Python, and each section will provide hours upon hours of valuable hands-on coding experience.

We will also be using Numpy for high-level computations and manipulation of high-dimensional arrays, Matplotlib for insightful charts, and Pandas to import, manipulate, and analyze datasets efficiently.

— Who is this Course for? —

You can see that there are many tools available in this space. Deep Learning This course will teach you the most important, most advanced ones. Deep Learning A-Z™ your skills are on the cutting edge of today’s technology.

If this is your first venture into the world of Deep LearningThis course will prove to be extremely valuable. Deep Learning A-Z™ is structured around special coding blueprint approaches meaning that you won’t get bogged down in unnecessary programming or mathematical complexities and instead you will be applying Deep Learning Techniques are taught very early in the course. You will gain a solid foundation and feel more confident as you go.

If you have previous experience with Deep LearningThis course is very practical, inspirational, and refreshing. Inside Deep Learning A-Z™ you will master some of the most cutting-edge Deep Learning There are many algorithms and techniques that didn’t exist one year ago. You will get a lot of hands-on experience dealing with real-world business problems. In addition, you will find inspiration and a way to try new things. Deep Learning Skills and applications

Real-World Case Studies

Mastering Deep Learning Knowing the tools and intuition is only part of the equation. It’s about being able apply these models in real-world situations to get tangible results for the project or business. This course introduces six new challenges.

#1 Churn Modelling Problem

This part will help you solve a data analysis problem for a bank. The bank will provide a large sample of its customers to help you create a data set. The bank collected information about the customers, including their credit scores, gender, age and tenure. It also asked for details such as credit card numbers, credit cards, credit card statuses, credit history, credit score, credit rating, credit balance, credit card usage, and if they are active. The bank monitored these customers for 6 months to see if they left or stayed with the bank.

Your goal is to create an environment that encourages creativity. Artificial Neural Based on the geo-demographic information and transactions above, network that can predict if any customer will leave the bank. A ranking of all customers is required based upon their likelihood of leaving the bank. You’ll need to use this right Deep Learning Model, one that uses a probabilistic approach to modeling.

You will bring significant value to the bank if you are successful in this project. Apply your knowledge and skills Deep Learning The bank model may reduce customer churn.

#2 Image Recognition

This part will show you how to create a Convolutional Neural Network capable of detecting various objects in images. This will be implemented. Deep Learning A model to identify a cat and a dog in a collection of photos. You can reuse this model to detect other species. We will show you how by changing the pictures in your input folder.

You can train the same model using a set brain images to determine if there are any tumors. However, if you wish to use it for cats or dogs, you can take a photograph of your cat or dog and your model will be able predict which pet you have. We even tested it out on Hadelin’s dog!

#3 Stock Price Prediction

You will create one the most powerful. Deep Learning models. Even the possibility of creating them. Deep Learning model closest to “Artificial Intelligence”. Why is this? This model will be able to retain long-term memories, just like humans.

The branch of Deep Learning This is possible because it is Recurrent Neural Networks. The memory of classic RNNs was very short, making them neither popular nor powerful. However, Recurrent has seen a major improvement. Neural Networks The popularity of LSTMs (Long-Short Term Memory RNNs), which have completely transformed the game, is a result. We are thrilled to incorporate these cutting-edge deeplearning methods into our course!

This part will teach you how to create this super-powerful model and give you the challenge of using it to predict the actual Google stock price. Researchers at Stanford University have already faced a similar challenge and we will attempt to be at least as successful.

#4 Fraud Detection

According to a recent report published by Markets & Markets the Fraud Detection and Prevention Market is going to be worth $33.19 Billion USD by 2021. This is a large industry with high demand for advanced technology. Deep Learning The demand for skills will continue to rise. That’s why we have included this case study in the course.

This is the first section of Volume 2 Unsupervised Deep Learning Models. This is the business challenge: detecting fraud in credit cards applications. This will allow you to create a Deep Learning You will be given a data set that includes information about customers who apply for advanced credit cards.

These are the details that customers gave when they filled out the application form. This is your task: detect fraud in these applications. You will then be able to create a list of potential customers who may have cheated their applications at the end of the challenge.

#5 & 6 Recommender Systems

Good recommender systems are extremely valuable in today’s World. They can be used to suggest Amazon products or Netflix movies. Data Scientists are among the highest-paid professionals on the planet who can create them.

We will be working on a dataset with exactly the same features that the Netflix dataset. There are many movies and thousands of users who have rated movies. The ratings are rated from 1-5, just like the Netflix dataset. This makes the Recommender System harder to create than if it were simply based on ratings. “Liked” Or “Not Liked”.

Your final Recommender System will be able to predict the ratings of the movies the customers didn’t watch. Your predictions can be ranked from 5 to 1. Deep Learning The model will be able recommend movies to users. It is not easy to build such a powerful recommendation system so we are going to give it two chances. This means that we will create it with two different methodologies. Deep Learning models.

The first model will be Deep Belief NetworksPart 5 will focus on the more complex Boltzmann machines. Our second model will feature the AutoEncoders. These are my personal favorites. Their simplicity will amaze you, but their power and capabilities will impress.

It will also allow you to share it with your friends. You will only need to rate movies that you have already seen, enter your ratings into the dataset, and then execute your model. If you’re stuck on what movies to watch on Netflix, the Recommender System will show you which movies you would enjoy one night.

— Summary

It is a fun training program that includes intuition tutorials, practical exercises, and real-world case studies.

Get your instant download Deep Learning A-Z Hands-On Artificial Neural Networks

We are extremely excited about it Deep Learning We hope to see you in class!

Kirill & Hadelin

Who is this course for?

All are welcome to apply. Deep Learning
Students with at least high school math knowledge and who wish to start learning Deep Learning
Anyone at an intermediate level who is familiar with the basics and principles of Machine Learning Or Deep LearningThese include the more complex topics like logistic regression and linear regression. Artificial Neural NetworksBut, who wants to know more and explore all of the fields? Deep Learning
Anybody who is not comfortable with programming but is curious about it. Deep Learning and would like to use it easily on datasets
All college students who wish to pursue a career in Data Science
Anyone who is interested in advancing as a data analyst Deep Learning
All people who don’t feel satisfied at their jobs and want to be Data Scientists.
Anyone who wants to add value to their company by using powerful tools Deep Learning Tools
Anyone who wants to understand the potential of Exponential technology for business. Deep Learning In their business
Entrepreneurs who want to disrupt an industry with the best cutting edge technology Deep Learning Algorithms

Here’s What You Will Get In Deep Learning A-Z Hands-On Artificial Neural Networks