Deep learning, a subset of Machine Learning, is a neural network that attempts to imitate the human brain and enable systems that predict outcomes based on data inputs.
We use deep learning for advanced driving in our cars, fraud detection for our insurance and bank frauds, and targeted advertising that helps us generate higher revenue and grow businesses.
Earlier, a user had to adapt to a computer, and the experience wasn’t personalized or perceptual. Deep learning mimics certain audio and video information to make it a perceptual experience for the user and power different applications that make our lives easy.
What are Deep Learning Use Cases?
While the search engine Google uses deep learning to create recognition algorithms, Netflix uses them to generate recommendation algorithms for different users.
Deep learning is used across industries for speech recognition, image recognition, translation, predictive forecasting, and Analytics. Let’s take a look at the top 10 industries that have benefited from Deep Learning:
- Voice assistants
- Fraud prevention
- Automated driving
- Insurance claim estimation
- Prediction of health risks
- Medical detection and analysis
- Marketing and promotion
- PR and reputation management
- Personalized advertising
Careers & Job Profiles in Deep Learning
If you’re a deep learning enthusiast looking for a career in deep learning, you can consider the following:
- Data Engineer
- Data Scientist
- Data Analyst
- Research Analyst
- Software Developer
- NLP Engineer
- Business Intelligence Analyst
- Deep Learning Program Designer
- Computer Vision Engineer
- Deep Learning Manager/Team Lead
Now that you know deep learning is a must-have skill across industries, take a look at the courses that can help you level up and be one of the best in deep learning today
Udemy’s Deep Learning A-Z™
Deep Learning A-Z is known for its strong structure, powerful projects, hands-on coding tutorials, and in-course support. That makes it one of the top-rated courses and trusted by businesses worldwide,
With 22 hours of video, 34 articles, 169 lectures, and 5 downloadable resources, this course has empowered 348,565 students. To be eligible, you need to be fluent in high-school-level mathematics and have basic knowledge of Python.
With this course, you get the chance to work on real-life data sets using artificial neural networks to solve problems, convolutional neural networks for image recognition, and recurrent neural networks to predict stocks. That’s not all!
You’ll also learn how to use self-organizing maps, Boltzmann machines and stacked autoencoders (the brand-new technique in Deep Learning). This course will also equip you to work with important tools like Tensorflow, Pytorch, Theano, Keras, and Scikit-learn.
A Deep Understanding of DL
Another highest-rated deep learning course teaches you how to master deep learning using the Pytorch tool and an experimental scientific approach.
With 57.5 hours of video tutorials, 3 articles, and 1 downloadable resource, this course comes with a certificate of completion.
You’ll need an interest in deep learning and a Google account to start learning for this course. You’ll get access to a live Q&A session, lots of exercises and code challenges, and 8+ hours of Python tutorials.
Get intuitive learning of artificial neural networks using graphics, spaces, and numbers. Visualize your learning and get a grasp of deep, comprehensive projects. This course is perfect for machine-learning enthusiasts, aspiring data scientists, and data scientists willing to expand their library of skills.
Data Science: Deep Learning
This course will teach you how to build your first artificial neural network using pure Python and TensorFlow code. With 89 lectures and 12 hours of video tutorials, you’ll get full lifetime access and a certificate of completion.
To start this course, you need to know calculus derivatives, matrix arithmetic, probability, and access to Python and Nymphy.
Also, it’s recommended that you’re familiar with the content of Lazy Programmer Inc’s logistic regression course. It covers topics related to cross-entropy cost, gradient descent, neurons, XOR, donut.
Through this course, you’ll learn how to code a neural network using Google’s TensorFlow. You’ll also learn how deep learning really works and important terms like “activation”, “backpropagation” and “feedforward.”
Intro to Deep Learning
If you’re looking for a course that teaches you to build and train neural networks for structured data using Keras and TensorFlow, the Intro to Deep Learning is the one. All you need is 4 hours to complete this course!
This course is free and divided into six sections, each with an exercise and a tutorial. The instructor is Ryan Holbrook and he helps you prepare for computer vision.
If you’re already familiar with the “Intro to Machine Learning” course, this is a great course to build on. So, if you’re wondering what exactly this course will teach you, read on.
You’ll start with building blocks of deep learning and train your first neural network via Keras and TensorFlow. In addition, learn overfitting and underfitting to improve your performance and add special layers to stabilize training.
Also, learn binary classification to apply deep learning to common tasks. Through this course, you’ll also get access to bonus lessons to apply your newly learned skills.
Deep Learning Tutorial for Beginners
With 18 lessons and 2 hours of learning, Simplilearn’s Deep Learning Tutorial for Beginners is an intermediate-level course.
Image and video processing skills are covered in this course. To go into more detail, this course will teach you what’s deep learning, what are its many applications, what’s a neural network and different deep learning frameworks and algorithms, and how to ace Python.
There’s more! You’ll learn about TensorFlow, convolutional neural networks, recurrent neural networks (RNN), GANs, and all about Keras.
Plus, you’ll get exclusive insight into Deep Learning Interview Questions.
Deep Learning, Illustrated Series
Deep Learning by I. Goodfellow, Yoshua Benigo, and Aaron Courville is a part of the 13-book series: Adaptive Computation and Machine Learning Series.
|Deep Learning (Adaptive Computation and Machine Learning series)||$73.98||Buy on Amazon|
If you’re wondering why you should give this book a shot, Elon Musk, co-chair of OpenAI and CEO of Tesla and SpaceX, has reviewed this book as the only comprehensive book on Deep Learning. Perfect for learners and enthusiasts of machine learning, this book discusses a broad range of topics.
In addition to conceptual backgrounds, learn deep learning techniques like deep feedforward networks, regularization, sequence modeling, and practical methodology.
You’ll receive practical perspectives on applications like natural language processing, speech recognition, bioinformatics, and video games.
However, suppose you’re looking for information on theoretical topics such as Monte Carlo methods, the partition function, approximate inference, and deep generative models. In that case, this book will stun you with its vast and expansible descriptions.
Deep Learning With Python
Francois Chollet’s Deep Learning With Python is an opportunity to master deep learning skills from the creator of Keras.
|Deep Learning with Python, Second Edition||$47.99||Buy on Amazon|
This 504-page read is perfect for intermediate readers with basic Python understanding. This book will teach you how to perform image classification and image segmentation, time-series forecasting, text classification and machine learning, text generation, neural style transfer, and image generation.
When you get this book, you’ll also get access to a free eBook in different formats. Deep dive into how Keras works in real-life situations and get insights that suit beginners, intermediaries and experts alike!
Deep Learning: A Visual Approach
Written by Andrew Glassner, Deep Learning: A Visual Approach is an illustrated edition that teaches you how to solve deep learning problems without complicated math. It has enough conceptual and visual explanations to guide you to the heart of deep learning.
|Deep Learning: A Visual Approach||$73.38||Buy on Amazon|
Without the need for equations or programming, you’ll be able to grasp how to use text generators to create articles and stories.
Not only that, know-how image classification systems work to identify objects or subjects, how to use machine learning techniques in tandem with AI, and so much more.
Get ready to build intelligent systems that help us envision the future of AI and take the right steps forward.
Edureka’s Deep Learning Full Course
If you’re looking for a visual resource that’ll help you deep dive into the inner workings of AI, deep learning, and Tensorflow, consider Edureka’s deep learning course.
In no more than 6 hours, you’ll be able to grasp how to apply deep learning techniques in close coordination with AI and machine learning.
Not only that, but from real-life applications (speech recognition, image recognition, automatic translation) to the three types of machine learning (reinforced, supervised, unsupervised), you’ll know it all.
You’ll move over to complex techniques like perceptron learning algorithm – single and multi, and their use cases, along with TensorFlow code basics and examples. Plus, master top 8 deep learning frameworks, artificial neural networks, and working of RBMs.
Also, learned how to create models, and chatbots using TensorFlow, work on object detection and understand the framework behind natural language processing (NLP). That’s not all!
This 6-hour course will also help you prepare deep learning-related interview questions for a prospective job or project. So, all the best!
Master Deep Learning In Hours
Mastering deep learning can be challenging, but make it easy with the courses, YouTube tutorials, and books mentioned above. The courses can help you get industry exposure by providing a certificate of completion that can stand as testimony of your knowledge;
However, when you’re looking for unique solutions or want to dive deep into specific topics, read the books and make the most of the YouTube tutorials. With the right courses and resources, learning how to make deep learning work for you won’t take more than a few hours at best!
You may also explore the top In-demand skills required for AI professionals.