5 Quality & Comprehensive Deep Learning Resources

Data science is incomplete without Machine Learning. Machine learning is a form of Artificial Intelligence used in this field. This level of Artificial Intelligence is required to sort out data or identify patterns and is possible through the use of machine learning algorithms. Some machine learning algorithms are a must for every data scientist's toolkit. Regression, clustering, classification and neural networks are some algorithms used extensively. Of course, there are plenty more used in more advanced applications but we are here to focus on deep learning which revolves around neural networks. Knowing these algorithms is your first step to learning data science and even Artificial Intelligence. To learn deep learning from scratch, there are some resources you can use. These books are essential for your understanding of DL algorithms and underlying concepts. These books do not need you to have machine learning knowledge and explains everything clearly. Let us take a look at them and what all one can learn from them:

1. Deep Learning by Ian Goodfellow, Yoshua Bengio and Aaron Courville (Book-2016)

This is your book helps you learn everything from scratch. It covers the basics and talks about important resources to start your deep learning journey. It does not matter if you are clueless about deep learning. Experts have even termed this book as The Bible of Deep Learning. This is because it covers significant points and does not make one feel overwhelmed by the terms. Mathematical aspects like statistics, algebra, and probability are all also covered in this book. This book also ventures into the practical application aspect of DL. Natural Language Processing (NLP), Computer Vision, Speech recognition, recommendation systems, bioinformatics are examples. It is available online in HTML version as well as on Kindle and hardcover.

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2. Deep Learning Course by Udacity & Google

Google teamed up with Udacity to create this online deep learning environment. The best part is that the course is free. It is available for anyone interested in Deep Learning. Anyone interested in learning Machine and Deep Learning will find this course comprehensive. It covers everything from basics to all the complexities. The projects make use of the TensorFlow framework. Using such a platform helps in gaining invaluable practical and theoretical knowledge. Since it is an online self-paced course, one can do it anytime. Udacity and Google are leaders in their own fields. Udacity has several other courses on Deep Learning as well, which one can make use of. Google brings the best and straightforward conceptual knowledge through Udacity. So, this course is a must for tech and deep learning enthusiasts.

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3. Stanford University Online Open Course on Deep Learning

This course is for anyone willing to learn directly from the experts. This is another online course to get you started with Deep Learning. It has been established and completed by experts in this field. Deep learning professionals from Google, Stanford and Baidu have compiled this course. It offers video based online tutorials on algorithms in DL and ML. Andrew Ng, a professor at Stanford, has also contributed to this course. This course covers in detail the topics of regression and regularisation. Everything is covered from linear and logistic regression to other various applications. Getting knowledge from such courses is invaluable. Many scientists and professionals have come together to explain everything exhaustively. So, it is a complete package for deep learning enthusiasts.

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4. Deep Learning Tutorial by University of Montreal

This course was developed as a book in the LISA lab at University of Montreal. It covers the concepts of machine learning and delves deep into Artificial Intelligence. The book stresses on using the ‘Theano’ library for developing deep learning models. Theano is a library developed by the University in Python. Using the MNIST dataset as a starter for practice, the book explains its concepts. It also follows better data labelling and math conventions. Additionally, it also follows supervised and unsupervised algorithm learning paths. One can read it randomly and apply the concepts to the MNIST dataset downloaded. This book acts as the complete deep learning basics tutorial for enthusiasts. As the University has worked to develop the course into a book, one can learn concepts as they come. Segregation into different concepts based on the type of learning is a big plus for readers.

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5. WildML:

This website keeps people updated with latest problems and updates in Deep Learning. Google LLC’s ex-employee Denny Britz, who is also a Stanford graduate, is the brain behind this website. The website offers tips and techniques for a deep learning starter. Denny posts various tutorials and articles on Reinforcement Learning and Neural Networks. It also has a deep learning index on-site allowing users to be familiar with techniques in DL. Terms like backpropagation, Seq2Seq, pooling are few such examples. This site is a must for anyone wanting to learn about new issues addressable through Deep Learning. One can gain information related to the problem and learn and apply them as required. Additionally, Denny Britz also posts updates on his Twitter profile. One can follow him on Twitter as well to stay updated. This site covers the basics as well as latest issues in Deep Learning.

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Conclusion:

These books and sites are comprehensive for clarity on Deep Learning concepts. One can continue learning through several sites and books. However, we have to start somewhere to understand and build a foundation of the concepts. These resources are great at establishing your foundation in Deep Learning. Since Artificial Intelligence, Machine and Deep Learning are interwoven, Data Science and Deep Learning algorithms are a must for anyone willing to learn and apply. Algorithms are the background of concepts in this field. One needs to know certain algorithms as well as Statistics. These sites and books take care of such things as best as possible and required. For further information one can look to for Deep Learning Courses In Kolkata at our centers. We offer Deep Learning courses as well as Artificial Intelligence courses.

 

Resources:

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