Description

Rggedu/ProEDU -Master Collection | 100 Custom Photoshop Textures

Rggedu/ProEDU -Master Collection | 100 Custom Photoshop Textures
Category: Tutorial
English | Size: 1.2GB
Handcrafted by Kelly Robitaille
Renowned beauty retoucher and PRO EDU instructor, Kelly Robitaille has developed a collection of 100 custom textures for Photoshop. Textures offer endless creativity in post production allowing you to create backgrounds, achieve Kelly’s signature look, or simply add visual interest, depth, and color to your final images.

Extension apks: To be installed with SAI tool (Split APKs Installer)

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.

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.

Your goal is to make an Artificial Neural Network that can predict, based on

geo-demographical and transactional information given above, if any individual customer will leave the bank or stay (customer churn).