Packt – Deep Learning With Java

Packt – Deep Learning With Java-JGTiSO
English | Size: 405.51 MB
Category: Tutorial


Learn
Extract features from unstructured data using ND4J
Use DL4J to perform fast and efficient deep learning training
Perform automatic speech recognition with DL
Use RNN with DL to achieve more precise results based on previous history
Process image data using multiple layers with DL4J
Use Word2Vect to perform feature extraction on text data
Predict using classification with a multilayered approach
About
Deep learning (DL) is used across a broad range of industries as the fundamental driver of AI. Being able to apply deep learning with Java will be a vital and valuable skill, not only within the tech world but also the wider global economy, which depends upon solving problems with higher accuracy and much more predictability than other AI techniques could provide. [Read more…]

Packt – Implementing Deep Learning Algorithms with TensorFlow 2.0

Packt – Implementing Deep Learning Algorithms with TensorFlow 2 0
English | Size: 785.19 MB
Category: E-learning


Learn
Understand what Deep Learning and TensorFlow 2.0 are and what problems they have solved and can solve
Study the various Deep Learning model architectures and work with them
Apply neural network models, deep learning, NLP, and LSTM to several diverse data classification scenarios, including breast cancer classification; predicting stock market data for Google; classifying Reuters news topics, and classifying flower species
Apply your newly-acquired skills to a wide array of practical and real-world scenarios [Read more…]

PluralSight – Deep Learning Instances and Frameworks on AWS

PluralSight – Deep Learning Instances and Frameworks on AWS-BOOKWARE-KNiSO
English | Size: 173.88 MB
Category: Tutorial


Release Notes: Deep learning enables a new level of data analysis, but configuring custom compute resources to gain these insights can be extremely difficult. In this course, Deep Learning Instances and Frameworks on AWS, you will gain the ability to launch deep learning instances on EC2 and ECS. First, you will learn the types of Deep Learning AMIs provided by AWS Next, you will analyze how to leverage popular deep learning frameworks on these instances. Finally, you will review how to manage and scale your deep learning activities on these instances. When you are finished with this course, you will be able to launch and utilize custom deep learning instances and leverage popular deep learning frameworks [Read more…]

Packt – Deep Learning with Real World Projects

Packt – Deep Learning with Real World Projects-XCODE
English | Size: 7.67 GB
Category: Tutorial


Learn
Learn to create Deep Neural networks and machine learning models for complex real-world problems
Get comfortable with Deep Learning libraries like TensorFlow and Keras
Learn inner workings of Convolutional Networks and Computer Vision
Work with AlexNet, GoogleNet, and ResNet
Recurrent Neural Networks
About
Deep learning is an artificial intelligence function that mimics the inner workings of the human brain in processing data and creating patterns for use in decision making. Deep learning is a subset of machine learning in artificial intelligence (AI) that has networks of interconnected nodes capable of un-supervised learning from data that is unstructured or unlabelled training data. It also enables representation of data in form of abstract features and classifies them into sub-classes which may be too complex for traditional machine learning models. [Read more…]

Packt – Autonomous Cars Deep Learning and Computer Vision in Python

Packt – Autonomous Cars Deep Learning and Computer Vision in Python-JGTiSO
English | Size: 3.20 GB
Category: Tutorial


Learn
Automatically detect lane markings in images
Detect cars and pedestrians using a trained classifier and with SVM
Classify traffic signs using Convolutional Neural Networks
Identify other vehicles in images using template matching
Build Deep Neural Networks with Tensorflow and Keras
Analyse and visualize data with Numpy, Pandas, Matplotlib, and Seaborn
Process image data using OpenCV
Calibrate cameras in Python, correcting for distortion
Sharpen and blur images with convolution
Detect edges in images with Sobel, Laplace, and Canny
Transform images through translation, rotation, resizing, and perspective transform
Extract image features with HOG
Detect object corners with Harris
Classify data with Machine Learning techniques including regression, decision trees, Naive Bayes, and SVM
Classify data with Artificial Neural Networks and Deep Learning
About
The automotive industry is experiencing a paradigm shift from conventional, human-driven vehicles into self-driving, artificial intelligence-powered vehicles. Self-driving vehicles offer a safe, efficient, and cost-effective solution that will dramatically redefine the future of human mobility. Self-driving cars are expected to save over half a million lives and generate enormous economic opportunities in excess of $1 trillion dollars by 2035. The automotive industry is on a billion-dollar quest to deploy the most technologically advanced vehicles on the road. [Read more…]

Packt – Deep Learning and Neural Networks Using Python Keras the Complete Beginners Guide

Packt – Deep Learning and Neural Networks Using Python Keras the Complete Beginners Guide-JGTiSO
English | Size: 4.27 GB
Category: Tutorial


Deep learning and data science using a Python and Keras library – The complete guide from beginner to professional
The world has been obsessed with the terms “machine learning” and “deep learning” recently. We use these technologies every day, with or without our knowledge. Ranging from Google suggestions, to translations, ads, movie recommendations, friend suggestions, sales and customer experiences. There are tons of other applications too so there’s no wonder that deep learning and machine learning specialists, along with data science practitioners, are the most sought-after talent in the current technology world. But the problem is that, when you think about learning these technologies, there is a common misconception that it’s a prerequisite to study lots of maths, statistics, and complex algorithms. It’s almost like someone making you believe that you must learn the working of an internal combustion engine before you learn how to drive a car. The fact is that, to drive a car, we just only need to know how to use the user-friendly control pedals extending from the engine like the clutch, brake, accelerator, steering wheel, and so on. And with a bit of experience, you can easily drive a car. The basic know-how about the internal working of the engine is of course an added advantage while driving a car, but it’s not mandatory. [Read more…]

Deep Learning Plunge into Deep Learning

Deep Learning Plunge into Deep Learning
English | Size: 1.08 GB
Category: Tutorial


Interested in the field of Machine Learning and Deep Learning? Then this course is for you!

This course is designed in a very simple and easily understandable content.

You might have seen lots of buzz on deep learning and you want to figure out where to start and explore.

This course is designed exactly for people like you!

If basics are strong, we can do bigger things with ease.
[Read more…]

LinkedIn Learning Introduction to Deep Learning with OpenCV

LinkedIn Learning Introduction to Deep Learning with OpenCV-APoLLo
English | Size: 1.44 GB
Category: Tutorial


Deep learning is a fairly recent and hugely popular branch of artificial intelligence (AI) that finds patterns and insights in data, including images and video. Its layering and abstraction give deep learning models almost human-like abilities-including advanced image recognition. Using OpenCV-a widely adopted computer vision software-you can run previously trained deep learning models on inexpensive hardware and generate powerful insights from digital images and video. In this course, instructor Jonathan Fernandes introduces you to the world of deep learning via inference, using the OpenCV Deep Neural Networks (dnn) module. You can get an overview of deep learning concepts and architecture, and then discover how to view and load images and videos using OpenCV and Python. Jonathan also shows how to provide classification for both images and videos, use blobs (the equivalent of tensors in other frameworks), and leverage YOLOv3 for custom object detection. [Read more…]

SKILLSHARE Modern Deep Convolutional Neural Networks with PyTorch

SKILLSHARE Modern Deep Convolutional Neural Networks with PyTorch
English | Size: 573.01 MB
Category: Tutorial


Dear friend, welcome to the course “Modern Deep Convolutional Neural Networks with PyTorch”! In this course, you will learn:

What are convolutional neural networks and why do people need them
How to efficiently train them
What is the best way to regularize and speed-up training of neural networks
How we can improve the prediction quality

Warmly welcome! [Read more…]

Deep JavaScript Foundations, v3

Deep JavaScript Foundations, v3
English | Size: 3.46 GB
Category: Tutorial

Dive into the core pillars of the JavaScript language with Kyle Simpson, author of the popular, You Don’t Know JS, book series. You’ll learn JavaScript’s types, how to convert between them, and compare them with == and ===. You’ll also learn lexical scope and closure. As well as the objects oriented system (this, prototypes and classes).
[Read more…]