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The Best Answers to Your Most Crucial Deep Learning Questions

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Most people keep close eyes on the top of the fast-moving technology trends. There’s no doubt that deep learning is most trending buzzwords today. Deep learning has made a significant breakthrough and is applied in many areas like facial recognition, recognizing images and AlphaGo Games. Thus more and more people focus on deep learning and have great interests in teaching themselves. This post aims to find out the best answers about deep learning and give a starting point to those interested in learning deep learning.


Based on my experience, I think Quora is probably the the best source of free expert opinions out there as it is a vibrant question-and-answer website on any topic imaginable. There’s no doubt that many questions about web scraping are also arising on Quora. I have compiled the most commonly asked questions here, in hope that they’ll help guide you learn deep learning.

“What is deep learning?”


“Why is Deep Learning so popular and in demand these days?”


“What is the best way to learn machine learning and deep learning from scratch?”


“What are some good books/papers for learning deep learning?”

“Has there been any work on using deep learning for recommendation engines?”


“Does LinkedIn use Deep Learning?”


As you can see, many important considerations about deep learning are covered in questions, and even more in the answers. More enlightening questions are:


“What do you think of Deep Learning?”


“Is there something that Deep Learning will never be able to learn?”


“If deep learning is the future what is the need for machine learning methods like SVM, decision trees, Bayesian methods, Markov chain etc?”


If I had just one shot at advising someone to start learning deep learning, I would repeat the following question:

“What's the most effective way to get started with Deep Learning?”


Now that we’ve known many resources and answers online, how should we get to it?

  1. Findsomeone with moderate programming skills. Talk to someone with programming skills and discuss any subject about deep learning with them so that you could quickly jump in as a newbie.
  2. Though some people figure out various libraries embedding math is used universally, you needn’t understand the theory to implement deep learning tasks, I still recommend you learn some math knowledge like partial derivative.
  3. Some resources could give you a good starting point like Stanford’s online course CS231n, Deep Learning at Oxford 2015and Andrew Ng’s Coursera class. Also, some interesting online books like Neural Networks and Deep Learning could also give you an assistance to deep learning.
  4. Facilities and toolkits should also be available. Computer hardware should handle thousands of operations at the same time as they are highly parallelized. Some software come with examples of working neural networks could solve many problems like image classification. So you could download it and work with that, and also learn some experience from that.
  5. Get some data you need to to start your model. When you start to learn deep learning, you would findthat the secret of applying deep learning to different areas is specific data. To exactly solve your problem, you need to specialize and put the data together and stand up by using deep learning. You could either get the data from the publicly available dataset like Wikipedia or purchase it from the DaaS companies. If none of above is applicable for you, you could dig the data from the web yourself by using some web scraping software like io and Octoparse. 


Deep Learning is a popular topic and people are quite interested in it. Be careful to choose the resources and find someone to help you get started. Then picking with your own questions, you could get the data and solve the problems accordingly.

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