According to Wikipedia, deep learning (deep structured learning, hierarchical learning or deep machine learning) is a branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data by using multiple processing layers, with complex structures or otherwise, composed of multiple non-linear transformations.
Deep learning is sometimes defined as the intersection between machine learning and artificial intelligence. Many articles on deep learning can be found here. Below is our selection:
- 15 Deep Learning Libraries
- 10 Deep Learning Terms Explained in Simple English
- Implementing a Distributed Deep Learning Network over Spark
- An Introduction to Deep Learning and it’s role for IoT/ future cities
- Deep learning & XgBoost : Winning it hands down !
- Evolution of Deep learning models
- Deep Learning Applications for Smart cities
- Is deep learning a Markov chain in disguise?
- Step-by-step video courses for Deep Learning and Machine Learning
- Deep Learning: Intelligence from Big Data
- Deep Learning for Beginners, on Github
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Additional Reading
- What statisticians think about data scientists
- Data Science Compared to 16 Analytic Disciplines
- 10 types of data scientists
- 91 job interview questions for data scientists
- 50 Questions to Test True Data Science Knowledge
- 24 Uses of Statistical Modeling
- 21 data science systems used by Amazon to operate its business
- Top 20 Big Data Experts to Follow (Includes Scoring Algorithm)
- 5 Data Science Leaders Share their Predictions for 2016 and Beyond
- 50 Articles about Hadoop and Related Topics
- 10 Modern Statistical Concepts Discovered by Data Scientists
- Top data science keywords on DSC
- 4 easy steps to becoming a data scientist
- 22 tips for better data science
- How to detect spurious correlations, and how to find the real ones
- 17 short tutorials all data scientists should read (and practice)
- High versus low-level data science
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