Paul Mascetta – The Code of Influence Copywriting Deep Analysis

Paul Mascetta – The Code of Influence Copywriting Deep Analysis
English | Size: 539.60 MB
Category: Tutorial

Hi Guys Lancelot85 here with another upload
Paul Mascetta – Code of Influence Copywriting Deep Analysis
a Great Bonus for the product
what will you find in this torrent?
A Complete and Deep Analysis of all the techniques used in the Webpage Hypnosis Code
Product that sell thousand of dollars
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Packt – Advanced Deep Learning with Keras

Packt – Advanced Deep Learning with Keras
English | Size: 758.6 MB
Category: Programming | E-learning

Keras is an open source neural network library written in Python. It is capable of running on top of MXNet, Deeplearning4j, Tensorflow, CNTK, or Theano. Designed to enable fast experimentation with deep neural networks, it focuses on being minimal, modular, and extensible. [Read more…]

Deep Learning with Python [Packt]

Deep Learning with Python [Packt]
English | Size: 374.09 MB
Category: Misc Learning

Deep learning is currently one of the best providers of solutions regarding problems in image recognition, speech recognition, object recognition, and natural language with its increasing number of libraries that are available in Python. The aim of deep learning is to develop deep neural networks by increasing and improving the number of training layers for each network, so that a machine learns more about the data until it’s as accurate as possible. Developers can avail the techniques provided by deep learning to accomplish complex machine learning tasks, and train AI networks to develop deep levels of perceptual recognition. [Read more…]

Live Lessons – Deep Learning for Natural Language Processing Applications of Deep Neural Networks to Machine Learning Tasks

Live Lessons – Deep Learning for Natural Language Processing Applications of Deep Neural Networks to Machine Learning Tasks
English | Size: 8.59 GB
Category: CBTs

An intuitive introduction to processing natural language data with Deep Learning models Deep Learning for Natural Language Processing LiveLessons is an introduction to processing natural language with Deep Learning. These lessons bring intuitive explanations of essential theory to life with interactive, hands-on Jupyter notebook demos. Examples feature Python and Keras, the high-level API for TensorFlow, the most popular Deep Learning library. In the early lessons, specifics of working with natural language data are covered, including how to convert natural language into numerical representations that can be readily processed by machine learning approaches. In the later lessons, state-of-the art Deep Learning architectures are leveraged to make predictions with natural language data. [Read more…]

Deep Learning A-Z™ Hands-On Artificial Neural Networks

Deep Learning A-Z™ Hands-On Artificial Neural Networks
English | Size: 3.15 GB
Category: CBTs

Artificial intelligence is growing exponentially. There is no doubt about that. Self-driving cars are clocking up millions of miles, IBM Watson is diagnosing patients better than armies of doctors and Google Deepmind’s AlphaGo beat the World champion at Go – a game where intuition plays a key role.
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O’Reilly – Introduction to Deep Learning

O’Reilly – Introduction to Deep Learning
English | Size: 999.07 MB
Category: Learning machine

Deep learning neural networks have driven breakthrough results in computer vision, speech processing, machine translation, and reinforcement learning. As a result, neural networks have become an essential part of any data scientist’s toolkit. This video introduces neural networks created with Python and MXNet, a flexible and efficient deep learning library. The course explains what neural networks are, why they are powerful algorithms, and why they have a particular structure. It begins by introducing the core components of a neural network (i.e., nodes, weights, biases, activation functions, and layers) before showing you how to build a neural network in MXNet that solves a classic classification problem: identifying handwritten digits from grayscale images. Along the way, you’ll learn about the backpropagation algorithm and how neural networks learn. Prerequisites include a basic understanding of Python, linear algebra, and calculus. [Read more…]

Coursera – Neural Networks and Deep Learning by Andrew Ng

Coursera – Neural Networks and Deep Learning by Andrew Ng
English | Size: 609.04 MB
Category: Tutorial

If you want to break into cutting-edge AI, this course will help you do so. Deep learning engineers are highly sought after, and mastering deep learning will give you numerous new career opportunities. Deep learning is also a new "superpower" that will let you build AI systems that just weren’t possible a few years ago.
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Udemy – Advanced AI Deep Reinforcement Learning in Python

Udemy – Advanced AI Deep Reinforcement Learning in Python
English | Size: 518.25 MB
Category: Tutorial

This course is all about the application of deep learning and neural networks to reinforcement learning.

If you’ve taken my first reinforcement learning class, then you know that reinforcement learning is on the bleeding edge of what we can do with AI.

Specifically, the combination of deep learning with reinforcement learning has led to AlphaGo beating a world champion in the strategy game Go, it has led to self-driving cars, and it has led to machines that can play video games at a superhuman level. [Read more…]

Stanford Natural Language Processing with Deep Learning 2017

Stanford Natural Language Processing with Deep Learning 2017
English | Size: 7.32 GB
Category: Tutorial

Natural language processing (NLP) is one of the most important technologies of the information age. Understanding complex language utterances is also a crucial part of artificial intelligence. Applications of NLP are everywhere because people communicate most everything in language: web search, advertisement, emails, customer service, language translation, radiology reports, etc. There are a large variety of underlying tasks and machine learning models behind NLP applications. Recently, deep learning approaches have obtained very high performance across many different NLP tasks. These models can often be trained with a single end-to-end model and do not require traditional, task-specific feature engineering.
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Packt Publishing – Learning Path – Python – Machine and Deep Learning with Python

Packt Publishing – Learning Path – Python – Machine and Deep Learning with Python
English | Size: 3.00 GB
Category: CBTs

Do you want to explore the various arenas of machine learning and deep learning by creating insightful and interesting projects? If yes, then this Learning Path is ideal for you!
Machine learning and deep learning gives you unimaginably powerful insights into data. Both of these fields are increasingly pervasive in the modern data-driven world. [Read more…]