Description

Shane Melcher – Facebook Messenger Marketing For Business Automation

Shane Melcher – Facebook Messenger Marketing For Business Automation | 4.83 GB

After Seeing Fake ‘Gurus’ Taking Advantage of People, I Knew I had to Do Something…Automate the Game!
So I made this for you….plus you get our expert ninja chatbot templates all throughout the course.

As you can see, there are lots of different tools in the space of Deep Learning and in this course we make sure to show you the most important and most progressive ones so that when you’re done with Deep Learning A-Z™ your skills are on the cutting edge of today’s technology.

then you will find this course extremely useful. 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 from very early on in the course. You will build your knowledge from the ground up and you will see how with every tutorial you are getting more and more confident. you will find this course refreshing, inspiring and very practical. Inside

Deep Learning A-Z™ you will master some of the most cutting-edge

Deep Learning algorithms and techniques (some of which didn’t even exist a year ago) and through this course

you will gain an immense amount of valuable hands-on experience with real-world business challenges. Plus, inside you will find inspiration to explore new Deep Learning skills and applications.

Mastering Deep Learning is not just about knowing the intuition and tools, it’s also about being able to apply these models to real-world scenarios and derive actual measurable results for the business or project. That’s why in this course we are introducing six exciting challenges:

In this part you will be solving a data analytics challenge for a bank. You will be given a dataset with a large sample of the bank’s customers. To make this dataset, the bank gathered information such as customer id, credit score, gender, age, tenure, balance, if the customer is active, has a credit card, etc. During a period of 6 months, the bank observed if these customers left or stayed in the bank.