10X Growth Conference 3 by Grant Cardone
Original price was: $999.00.$49.00Current price is: $49.00.
This Course is available for download now. You can contact us for Screenshots or Demo. Access for this course will be sent on google drive. Join our telegram channel to see updates and occasional discounts. If you want to pay through Paypal or Card contact us – On Telegram Click Here or contact on Mail – [email protected]
Description
10X Growth Conference 3 by Grant Cardone
Grant Cardone – 10X Growth Conference 3 | 45.2 GB
RELIVE THE LARGEST BUSINESS CONFERENCE EVER!
Get 10X Growth Conference 3 Official Recording
ABOUT THE 10X MOVEMENT & GRANT CARDONE
10X is the right think, combined with the right amount of actions across all of your life?s interests, to accomplish an extraordinary life; referred to as a 10X Super Life.
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). Besides, you are asked to rank all the customers of the bank, based on their probability of leaving. To do that, you will need to use the right Deep Learning model, one that is based on a probabilistic approach.
If you succeed in this project, you will create significant added value to the bank. By applying your Deep Learning model the bank may significantly reduce customer churn.
In this part, you will create a Convolutional Neural Network that is able to detect various objects in images. We will implement this Deep Learning model to recognize a cat or a dog in a set of pictures. However, this model can be reused to detect anything else and we will show you how to do it – by simply changing the pictures in the input folder.
For example, you will be able to train the same model on a set of brain images, to detect if they contain a tumor or not. But if you want to keep it fitted to cats and dogs, then you will literally be able to a take a picture of your cat or your dog, and your model will predict which pet you have. We even tested it out on Hadelin’s dog!