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Free Online Resources To Get Hands-On Deep Learning

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Free Online Resources To Get Hands-On Deep Learning

Illustration by Free Online Resources To Get Hands-On Deep Learning

With deep learning gaining its momentum in fields like self-driving cars, object detection, voice assistants and text generation, to name a few, the demand for deep learning experts in organisations has also significantly increased. As a matter of fact, big tech companies like Facebook, Google, Apple as well as Microsoft have started investing heavily on deep learning projects which, in turn, increase the number of deep learning open jobs in the market.

Having said that, deep learning is one of the complex subsets of machine learning and envelops several layers of components which cannot be grasped in a day. Hence, despite the high demand, there is indeed a gap in deep learning talent for organisations. Not only does it come with prerequisites of linear algebra and calculus knowledge but also enough interest to pursue a complicated subject like deep learning.

Therefore, in order to help enthusiasts and aspirants to get their hands on deep learning, Analytics India Magazine curated eleven free resources available online. Here is a list, in no particular order:

Also Read: A Guide To Switching Careers To Deep Learning

Deep Learning Tutorial

Offered by: Simplilearn

About: Deep Learning Tutorial is a free tutorial provided by Simplilearn with Keras and TensorFlow. With this tutorial, the learners will be introduced to deep learning, its purpose and the learning outcomes with a deep learning certification. It covers topics such as in-depth knowledge of TensorFlow, implementing linear regression and gradient descent, implementing deep learning algorithms, training deep networks, providing a comprehensive understanding of deep learning with Keras and TensorFlow.

Click here to know more.

Python Deep Learning

Offered by: TutorialsPoint

About: Python has been a preferred language in data science and for producing deep learning algorithms. This tutorial will introduce learners to Python and its libraries NumPy, SciPy, Pandas etc. to solve real-world problems using deep learning frameworks. Offered by TutorialsPoint, this tutorial has been designed for professionals who are willing to learn the basics of Python and develop deep learning techniques. It comes with specific prerequisites of basic knowledge of linear algebra, calculus, statistics and basic machine learning techniques.

Click here to know more.

MXNet Tutorial: Hands-On Implementation of Deep Learning Framework

Offered by: Analytics India Magazine

About: In this tutorial, an aspiring data scientist explains MXNet and its implementation on random data. Starting with an overview of the open-source deep learning framework — MXNet, this course will dive into generating random data and using the python programming language for understanding deep learning programming paradigm and MXNet system architecture.

Click here to know more.

Deep Learning Full Course in 6 Hours

Offered by: Edureka

About: Deep Learning Full Course in 6 Hours is a Youtube tutorial offered by Edureka, that will provide the learners with a comprehensive knowledge of deep learning and TensorFlow. Starting with the introduction of deep learning, machine learning and artificial intelligence, this course will teach supervised learning, reinforcement learning, perceptron learning algorithm, backpropagation, to deep learning frameworks. This tutorial will also teach how to create a deep learning model for significant use cases.

Click here to know more.

Also Read: Deep Learning DevCon 2020: Virtual Conference by Association of Data Scientists

Deep Learning Tutorial for Beginners

Offered by: Kaggle

About: Deep Learning tutorial for beginners is a comprehensive tutorial offered by Kaggle. This course leverages Python notebook using data from Sign Language Digits Dataset. This tutorial started with the introduction of the technology and followed by logistic regression, optimization algorithm with gradient descent, and artificial neural network. Rather than writing big paragraphs, this course consists of significant keywords in every line, which provides a practical experience for learners.

Click here to know more.

Deep Learning Tutorials

Offered by: DeepLearning.Net

About: This deep learning tutorial will introduce learners to some of the most critical deep learning algorithms and will also teach how to run them using Theano — a Python library. Being familiar with Python is one of the prerequisites this tutorial comes with; however, one can also get a Theano tutorial along with it. This tutorial is compatible with Python 2 and 3 except for modelling and generating sequences of polyphonic music with the RNN-RBM, which is only available only for Python 2.

Click here to know more.

Deep Learning Tutorial

Offered by: Great Learning

About: This is again a nine hours YouTube tutorial offered by Great Learning which will provide full knowledge of deep learning. Not only it will teach theoretical knowledge on the technology but will also showcase how to install Python and other IDEs, along with data structures in Python and its functions. This tutorial will also provide a demo on wine dataset using Keras sequential model, along with backpropagation and gradient descent algorithm, and a demo on MNIST dataset.

Click here to know more.

Keras With Tensorflow

Offered by: Deeplizard

About: This tutorial, aka a free course, that will teach learners how to use Keras, a neural network API in Python. This comes with text and video resources on a deeplizard’s website, along with a video playlist on YouTube, which focuses on specific concepts and the workflow of using Keras and Python. It starts with the basics of organising and processing data and then dives into building and training neural networks. While this free course comes with a prerequisite of basic knowledge of deep learning, it also offers a fundamentals course first, before one takes this ahead.

Click here to know more.

MIT Deep Learning Basics with TensorFlow

Offered by: Lex Fridman

About: This tutorial is a part of MIT Deep Learning series, led by the research scientists at MIT, that consists of various lectures, classes and tutorials covering basics of deep learning and neural networks. With an overview of deep learning technology in seven architectural paradigms with TensorFlow tutorials for each of them, this course will also cover topics like — Feed Forward Neural Networks; Convolutional Neural Networks; Recurrent Neural Networks; Encoder-Decoder Architectures; Generative Adversarial Networks; Deep Reinforcement Learning, etc.

Click here to know more.

Deep Learning Tutorial

Offered by: Stanford

About: With contributed materials from Andrew Ng, Jiquan Ngiam, Chuan Yu Foo, and other experts of the industry, this tutorial will cover the main ideas of unsupervised feature learning and deep learning. The tutorial will also provide hands-on experience in implementing several feature learning/deep learning algorithms to solve real-world problems. This tutorial comes with a prerequisite of basic knowledge on machine learning with familiarity with supervised learning, logistic regression, gradient descent. If learners are struggling with these necessary steps, this tutorial also offers an additional machine learning course for comprehending these subjects first.

Click here to know more.

Deep Learning With PyTorch: A 60 Minute Blitz

Offered by: PyTorch

About: Coming from the core team of PyTorch, this 60-minute tutorial is perfect for getting a quick understanding of the library as well as practical workings on training neural networks to classify images. Covering topics like a convolutional neural network, loss function, and single and multiple GPU training, this tutorial provides the basic knowledge one requires to get their work started. Although it isn’t an advanced tutorial with comprehensive knowledge, it surely helps novices beginning their career in deep learning.

Click here to know more.

PS: The story was written using a keyboard.
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Sejuti Das

Sejuti currently works as Associate Editor at Analytics India Magazine (AIM). Reach out at sejuti.das@analyticsindiamag.com
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