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LinkedIn Lead Challenge by Jimmy Coleman

Jimmy Coleman – LinkedIn Lead Challenge | 5.53 GB

Whether it is a 1-on-1 call, flying out to train your team, or hiring Jimmy as a fractional CMO click below to discuss your needs and how we can help. This process has generated over 10 million dollars for some companies. If your team has the ability to invest to maximize your ROI, schedule a call with our team an we will create a consulting package that best suits your team.

Create an input form – have it update your page elements – have fun while learning element selection and manipulation. The DOMinator is a set of input fields with buttons that connect to page elements allowing you to update the content and add classes. Create a web interface to select and update elements from the webpage. Add and remove elements using the form input and select options. Demonstrates how to apply DOM manipulation, make element selection all while creating a fun interactive web application.

So many courses and books just bombard you with the theory, and math, and coding… But they forget to explain, perhaps, the most important part: why you are doing  And that’s how this course is so different. We focus on developing an intuitive *feel* for the concepts behind Deep Learning algorithms.

With our intuition tutorials you will be confident that you understand all the techniques on an instinctive level. And once you proceed to the hands-on coding exercises you will see for yourself how much more meaningful your experience will be. This is a game-changer.

Are you tired of courses based on over-used, outdated data sets?

Yes? Well then you’re in for a treat.

Inside this class we will work on Real-World datasets, to solve Real-World business problems. (Definitely not the boring iris or digit classification datasets that we see in every course). In this course we will solve six real-world challenges:

• Artificial Neural Networks to solve a Customer Churn problem
• Convolutional Neural Networks for Image Recognition
• Recurrent Neural Networks to predict Stock Prices
• Self-Organizing Maps to investigate Fraud
• Boltzmann Machines to create 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 which didn’t even exist a couple of years ago. We haven’t seen this method explained anywhere else in sufficient depth.

In Deep Learning A-Z™ we code together with you. Every practical tutorial starts with a blank page and we write up the code from scratch. This way you can follow along and understand exactly how the code comes together and what each line means.