How to Learn Deep Learning: Courses, Job Opportunities, and More
There’s a world of data out there and it’s always going to need sorting. This data can help businesses make decisions about offerings, efficiency, or what’s best for their customers.
Humans only have so much time and energy in a day. Machines never get tired when analyzing data and making decisions. How can we get these machines to operate smoothly and efficiently without constant instruction? We use deep learning. Read below to learn how you can use deep learning to your advantage.
What Is Deep Learning?
Deep learning is a subset of machine learning patterned after the human brain. It uses artificial intelligence (AI) to make decisions based on massive data sets. Neural networks, computer systems built to function like a human brain, make deep learning possible.
Neural networks have hundreds or even thousands of nodes that are connected by an internal web, much like the neurons in the human brain. These nodes are arranged to take in information and then translate it into the right output.
These networks can be designed to work with or without supervision. There are several different architectures and deep learning models. Deep learning is versatile, and different methods have different uses based on how smart or resource-heavy they are.
What Is Deep Learning Used For?
Deep learning is used to find patterns in data to improve a system or product. Plenty of companies use deep learning algorithms to save time and money sorting data. Almost every industry requires some sort of data sorting and analysis, so deep learning is a useful skill.
One of the most famous deep learning research teams is Google Brain, which was founded in 2011. It has been used for many different projects because the team works on an individual basis. In 2012, Google Brain recognized a cat based on 10 million images from YouTube.
Deep learning has several uses in the finance sector, from forecasting the stock market to fighting financial fraud. By feeding the neural network current and past information about the stock market, it can suggest stocks that might be a good investment.
Banks use deep learning to check for discrepancies or inordinate spending from accounts. If you’ve ever received a fraud warning that saved you thousands of dollars, it happened because of deep learning.
In 2016, the Google Brain project gave us some very promising research. They ran three neural networks simultaneously: two were tasked to communicate, and the third tried to intercept the messages. After a while, the two communicators developed their own encryption methods on their own.
Researchers continue to find ways to use deep learning and encryption. If humans don’t create the encryption, then how can they know how to crack it?
Learn Deep Learning: Step-by-Step
We’ve discussed some of the ways that deep learning is being used to improve our lives. This is a versatile and endlessly useful concept for everyone to know. Here’s how you can do your own deep learning to become an expert at the process.
1. Learn the Different Types of Deep Learning Models
If you’re interested in deep learning, you should first learn about the three different deep learning models and how they’re used in the industry.
- Recurrent neural networks (RNN) process sequential data, which makes them great for applications that take place over time, like automatic captioning or answering questions via Siri.
- Artificial neural networks (ANN) are trained to look for patterns and give a yes or no answer, and they’re used to classify images or recognize fraud.
- Convolutional neural networks (CNN) filter inputs like photos or videos in order to provide detailed information, like identifying a person in a picture.
2. Learn to Build Hardware
You have two options when it comes to selecting your deep learning hardware. You could pay a cloud computing service like AWS or Microsoft Azure to host your model. Or, you could learn to build your own deep learning computer.
Deep learning networks require lots of processing power, so they need more GPU than a standard computer. The reason GPUs are so important here is because machines use processing cores to do their work. You can find several guides online to teach you how to build these machines.
3. Learn to Build the Software of your Deep Learning Project
After you’ve got the hardware, it’s time to focus on building your software. Online courses are a great way to find out how.
Plenty of online courses can teach you how to build your own machine learning architectures. You’ll learn how to build several different types of models from the ground up, and you can see which ones are right for you.
The Best Deep Learning Courses
There are tons of great deep learning courses out there, and some of them are free. These courses will usually teach you how to build a small scale deep learning model that can run on any PC. If you wanted to run a large scale project down the road, you’d have to invest in more infrastructure.
This free course from Andrew Ng, co-founder of Google Brain and Coursera, gives beginners an intro to the world of AI. You’ll learn about deep learning, neural networks, and more. This course will also teach you about the capabilities and ethics of AI and how to incorporate it into your workflow. With one of the architects of the biggest deep learning projects in the world, you’ll be ready to conquer anything that comes your way.
If you have some experience with coding in Python, this course may be exactly what you’re looking for. It will show you how to use tools in Python to perform different tasks. You’ll build a movie-recommender system, a deep learning model that can classify images, data, and sentiments. You’ll also create a Pac-Man bot that takes advantage of reinforcement learning technology. If you enjoy hands-on learning, this is a great option.
This certificate from IBM covers the fundamental concepts, methods, and uses of deep learning. You’ll also learn more about deep learning on a large scale with GPUs, accelerated hardware, and Python libraries. You should have no problem mastering big data after going through this certification process. Certificates look great on every resume, so if you’re entering the job market, this is a great choice.
This course is for those who want to learn more about deep learning’s financial capabilities. You’ll be able to use artificial intelligence to make predictions, help manage financial risk, and optimize portfolios. This is a short course, so you should be able to hop into the finance world right away.
Is Deep Learning Right for You?
Deep learning is a set of practical technologies with a host of uses in the real world that we encounter every day. Deep learning keeps your money safe, helps you find the correct Google result, and more.
If you decide to get into deep learning, you could find a job working for some of the top tech companies in the industry. You could also enter the finance sector and build your own machine to bring you to stock success. If you’re an innovative hard worker, deep learning is the right way to go.