Chad Kimball – 1 on 1 Chad PBN Training
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Description
Chad Kimball – 1 on 1 Chad PBN Training
Chad Kimball – 1 on 1 Chad PBN Training | 131 MB
DON?T BELIEVE WHAT ? EVERYONE SAYS??ABOUT PRIVATE BLOG NETWORKS.
1. ?Everyone says? PBNs will get your site penalized.
2. ?Everyone says? Google is deindexing all PBNs.
3. ?Everyone says? PBNs just don?t work anymore.
If what ? ?everyone says? is true?.why do so many big player STILL us their own Private Blog Networks?
HERE?S THE HONEST TRUTH.
1. Most penalized sites aren?t using real, private PBNs. They?re simply buying posts on pulic blog networks, which are easeily
discovered and penalized
2. Google has recently deindexed a number of poorly-buit or poor-hidden private PBNs.Properly-buit PBNs survived just fine.
3. PBNs still work wonders. That?s why almost all successful internet marketers still rely on them – and continue to build more of them
FORGET WHAT ? EVERYONE SAYS?. WELL BUILT PBNs ARE STILL THE KEY?TO LONG-TERM RANKINGS AND BIG MONEY ! That?s why the big players still rely on their own Private Blog Networks
WHILE WE?RE BEING HONEST?HERE ARE THE REAL PROBLEMS WITH PRIVATE BLOG NETWORKS
From Amazon product suggestions to Netflix movie recommendations –
good recommender systems are very valuable in today’s World. And specialists who can create them are some of the top-paid Data Scientists on the planet.
We will work on a dataset that has exactly the same features as the Netflix dataset: plenty of movies, thousands of users, who have rated the movies they watched. The ratings go from 1 to 5, exactly like in the Netflix dataset, which makes the Recommender System more complex to build than if the ratings were simply “Liked” or “Not Liked”.
Your final Recommender System will be able to predict the ratings of the movies the customers didn’t watch. Accordingly, by ranking the predictions from 5 down to 1, your Deep Learning model will be able to recommend which movies each user should watch. Creating such a powerful Recommender System is quite a challenge so we will give ourselves two shots. Meaning we will build it with two different Deep Learning models.
Our first model will be Deep Belief Networks, complex Boltzmann Machines that will be covered in Part 5. Then our second model will be with the powerful AutoEncoders, my personal favorites. You will appreciate the contrast between their simplicity, and what they are capable of.
And you will even be able to apply it to yourself or your friends. The list of movies will be explicit so you will simply need to rate the movies you already watched, input your ratings in the dataset, execute your model and voila! The Recommender System will tell you exactly which movies you would love one night you if are out of ideas of what to watch on Netflix!