Here are some resources to start learning Deep Learning:Free Online BooksDeep Learning by Yoshua Bengio, Ian Goodfellow and Aaron Courville (05/07/2015)Neural Networks and Deep Learning by Michael Nielsen (Dec 2014)Deep Learning by Microsoft Research (2013)Deep Learning Tutorial by LISA lab, University
Mike Leary in 2013 responded to a similar question in 2013:
Deep learning is also known as deep machine learning; it is a study of machine learning algorithms and artificial neural networks where more than one layer is hidden. These cascading layers are of nonlinear processing units which are utilized for
How did Google's DeepMind train AlphaStar to play Starcraft 2 with reinforcement learning and did that mean running the Starcraft game in an accelerated way billions of times to train the neural network?
From AlphaStar: Mastering the Real-Time Strategy Game StarCraft IIAlphaStar's behaviour is generated by a deep neural network that receives input data from the raw game interface (a list of units and their properties), and outputs a sequence of instructions that constitute an action within the game. More specifically, the
Machine learning is very big topic which can have the night scope in future.Machine learning is represent the ability to learn the human strategy,speech,behaviour,etc.Let me tell you how the machine learning works.Robot or machine is mainly understand the speech of the human
Like anything worth while in your life, your journey begins with the first step, seriously, that is all it takes, you MUST take that first step!If you have the desire and let yourself form a commitment to learning, whatever it is you want to learn, the journey will not be hard at all. It will
How should I get started with deep learning? Can someone guide me to Mathematics resources specifically for Deep Learning?
Follow the concept graph given in Metacademy Once you have understood the basics, read the two basic papers which introduce the ideas -1. a) A fast algorithm for learning deep belief nets & b) To recognize shapes first learn to generate images - Geoffrey Hinton 2006.Introduced the idea of layerwise
I have 25 hrs/ week to dedicate to learning Machine / Deep Learning (from scratch, CS & stats background). In how much time can I get a job in ML?
You can have a look into my blog post on AI/ML which is written considering beginners in mind. Feel free to ask any question or leave a feedback . links below-Basic Concepts of Artificial Intelligence, Machine Learning, Deep Learning10 Most Commonly Used Machine Learning Algorithmsalso wrote a python implementation -Linear Regression Implementation
Interpretation of deep neural network models (DNN) has always been a limiting factor for use cases. What are some methods and techniques that help to interpret the output of neural networks?
Core concepts will be highlighted - reasoning remains non-highlighted.There's numerous different methodologies that tend to illustrate what you are getting - based off of what kind of Metric you are inferring.An example would be Curve Fitting.If you were to literally, plot the Curves - and showcase how good of a
There was a paper written called No Free Lunch Theorems for Optimization (https://ti.arc.nasa.gov/m/profil...) that basically says that when considering optimization, all solutions, when averaged across all problems in the problem space, are the same. As the paper puts it,
The biggest misconception is they mimic how a brain processes information. Although they are inspired by networks of neurons, the gross simplifications of their organization, activation function, etc. makes neural nets more akin to elaborate curve fitting instead of actual neurons.Efforts to produce realistic neuron models do exist, but their purpose is more aligned with biology, not AI.
With machine learning and deep learning being probably the hottest trend going on in the computer science world right now, it's no surprise that many are looking to get involved in the field. When I first became interested in machine learning, I was overwhelmed by the tons of resources available
This is a great question, which is well covered by the press. I really like this summary, which supposedly is based on asking multiple experts.First, people seem to vastly overestimate what is achievable by machine learning. I elaborate on this in my recent Quora answer.Second, people think that machine learning is an
Google is a big company, so different teams use different languages. Deepmind, a Google acquisition, uses a flavor of Torch, which is written in Lua on top, and optimized in C/C++. Geoff Hinton mentioned, after he joined Google, that
How to Kick Start in Deep LearningMathFor understanding basic deep learning papers, it is important to be comfortable with basic concepts in linear algebra and calculus. Here is the good summary lists that cover basics topic that you should know.I would estimate, it perhaps take around
Not anytime soon!Yes, deep learning models are superior in accuracy to almost all other learning algorithms on almost all learning tasks. But this is not enough in practical situations!There are many problems with deep learning:1- It needs HUGE datasets to learn from:Neural nets can break records in
Well doing deep learning in the span of a hackathon is tricky--many problems take a long time to train. However, you can certainly train simple deep networks. Some ideas:1) simple robotics: given sensor inputs, train a neural network to decide the next action (forward, left,
What steps can be taken to over come the jobs lost due to artificial intelligence and machine learning?
I will answer in a few points:There will be a lot of training and teaching jobs created to have a specialized educated workforce. However, I imagine this can happen over online videos and resources rather than physical centers. People are already becoming