Learn Deep Learning: The Best Courses and Resources
When we make decisions in our everyday lives, our brains go through certain processes to sort relevant information and recognize patterns. Artificial intelligence and deep learning work in the same way, processing and creating patterns in an outside source.
Deep learning is how a computer learns algorithms, by using artificial neural networks that are inspired by the functions and structure of the human brain.
Whether you have heard of deep learning before and want to study it independently or have no idea what it is, then read on to find all the essential information, resources, and training courses that will help you get started.
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What Is Deep Learning?
Deep learning is a type of machine learning that mimics the workings of the human brain. The machines learn by processing big data through a natural language processing system that is used for tasks such as detecting objects, translating languages, and decision-making.
Deep learning uses artificial neural networks, which are also used in machine learning, to find patterns in unstructured data through computing power. Deep learning is different from earlier forms of AI because it is accomplished without any human interference. This field is a subset of machine learning.
Deep learning powers many of the services we use today, including YouTube, Netflix, Spotify, Baidu, Google, and Facebook.
What Jobs Use Deep Learning Skills?
Similar to how Google has its own algorithms to gather data in the back-end, other companies also use deep learning to collect information.
One example of how this works is in digital finance industries. If an organization wants to detect fraud in its systems, it can employ machine learning tools such as deep learning to find patterns in its data sets and locate any inconsistencies.
Machine learning and deep learning are closely related, so studying both will help you see the bigger picture.
As technology advances each year, so do deep learning methods. These methods are now used in many industries. A few of the jobs that have adapted deep learning are mentioned below.
- Social media and image classification. Tagging photos on social media is made possible through the process of image classification using deep learning. Image classification is when a computer analyzes an image and puts it into a class, such as animal, car, or building.
This process is used in most social media jobs, such as that of a social media analyst.
- Python engineer. A Python engineer will be well-versed in the programming language Python, which is commonly used in AI and deep learning.
Python developers must understand the data structures, algorithms, and computer architecture of a company to improve existing programs and build new ones that will help the organization.
- Data scientist. Data scientists apply their knowledge of statistics, programming, and mathematics to sort through big data using platforms such as Hadoop, Hive, Spark, and Flume.
- Machine learning researcher. Machine learning researchers build models that can interpret big data using algorithms and neural networks. They can work in a variety of sectors, such as finance or manufacturing.
Steps to Learn Deep Learning
If you want to work in deep learning, there are several steps you should take.
1. Learn Programming Skills
You must study programming languages such as Python and C++ to get started in deep learning. You should also gain cloud computing experience. To brush up on these topics, you can take an online course, such as Practical Deep Learning for Coders.
Tap into all the resources available to you, such as university websites, YouTube videos on machine learning and AI, and books.
2. Study Calculus and Linear Algebra
Basic math skills such as algebra and calculus are also essential to deep learning. You can also look at online courses and videos if you are not strong in these areas. You may need to dedicate at least 20 hours a week over the next six months to become an expert in these subjects.
3. Choose an Area to Specialize In
Instead of trying to learn everything about deep learning, choose a specific area that interests you. For instance, if you’re passionate about visuals, you might want to learn about Computer Vision. This field deals with how computers can gain high-level understanding from videos and digital images.
Similarly, if you’re into music or video games, you might want to look into specific learning paths that combine these subjects with deep learning. For example, Spotify uses AI, as does gaming giant NVDIA, which also offers hands-on training in AI.
4. Build Something
As an expert in machine learning, you will need to build neural networks. This could be a simple Twitter sentiment analysis using neural networks such as CNN or RNN. Or, you could even compose music using recurrent neural networks.
Some of the most cutting edge technologies that are now popular use deep learning models.
The Best Courses to Learn Deep Learning
Taking a course in deep learning and getting a qualification is highly recommended if you want the right skills to get a job in deep learning. Below, we have compiled a list of some of the best deep learning courses.
If you’re interested in learning from one of the most prominent graphics processing unit developers, then NVIDIA is a great choice.
NVIDIA’s learning institute offers courses on data science, accelerated computing, and AI. Whether you’re a student or are already employed in machine learning, you can get practical experience from these classes and earn a certificate.
The institute has instructor-led classes, online courses, and university training options.
If you do not have a background in high-level mathematics or technology, that’s OK. This course is open to anyone who has a basic knowledge of Python and a knowledge of high school math.
In this course, you will learn everything from natural language processing to computer vision. These topics will help you land a job in many fields, from medicine to robotics and gaming. There is also a second course in this series, called Part 2: Deep Learning From the Foundations.
This Google crash course in machine learning is divided into several video lectures, lasting from between 15 minutes to 1 hour.
The course covers everything about machine learning, including the benefits of mastering the subject and the philosophy behind it. You will get free access to the resources, so you can learn at your own pace.
Learning the key concepts and algorithms of AI is fundamental to deep learning. Without it, you won’t be able to understand neural networks. Deeplearning.ai offers five courses taught by experienced lecturer Dr Andrew Ng.
OpenDataScience has made studying machine learning easy. This organized and balanced course teaches theory and includes practical assignments at the end of each module.
The lectures are taught by senior machine learning scientist Yury Kashnitsky, and the site also offers other resources such as materials, and tutorials.
Other Deep Learning Resources
Another way to learn about AI and deep learning is by joining a few relevant online communities. One example is the Slack group by the Open Data Science team. In it, participants share projects and information on the latest machine learning courses.
There are also a few other data sciences Slack communities you may want to join.
Reddit is also known for information sharing in its small groups, such as Reddit r/MachineLearning. In this forum, you can read comments from others studying deep learning, and add your own into the mix.
Once you join, you will have access to the community’s library of resources that you can browse in your spare time to keep up with your personal development.
The ParallelDots website has a list of popular blog pages you can read to improve your knowledge of deep learning. These websites are a good way to stay up to date with the tech industry and global AI developments. These blogs cover everything from research, implementation, and future prospects of AI.
Why Learn Deep Learning?
Trying to understand AI can be difficult, and learning the subfield of deep learning takes commitment.
Deep learning has taken precedence over most other processing technologies due to its higher rate of accuracy when trained with big data. This method allows Facebook to recognize your friends, and Netflix to suggest which series you may want to watch next.
So, why should you learn deep learning? It can handle complex problems better than traditional computers and has already been implemented in many industries.
It is expected to expand significantly over the next 10 years in the fields of medicine, automotives, sports, security and surveillance, fashion, and agriculture. If you’re looking for job security in a fast-growing industry, then deep learning is a reasonable tech career choice.