TensorFlow is one of the best resources for machine learning, but many people struggle with balancing their learning with everything else. To help you, we’ve established some great ways to help you learn TensorFlow fast.
Let’s dive into what you need to learn about TensorFlow and where and how you can learn about the foundations.
What Is TensorFlow?
TensorFlow is a method for beginners and experts alike to expand their machine-learning knowledge. With a wide range of tools at your disposal, TensorFlow is a great way to learn machine learning principles and core concepts. Many companies use TensorFlow to develop their skills.
You can learn how to make models for the web, for the cloud, for smartphones, and for production. There are many tutorials to learn from, but you may be wondering how to learn them fast.
Many beginners are intimidated by the range of material on TensorFlow. To help you learn fast, we’ve compiled this helpful guide to utilize your time to the best of your ability.
How To Learn TensorFlow Fast?
If you want to learn TensorFlow fast and utilize your time and money to the best of your ability, you will need to work hard. Thankfully, it’s become easier than ever to learn from resources quickly.
To help you pool your resources, we’ll give you the best resources available to help you during the learning process so you can maximize your time.
Learn Python Programming
Before you start with TensorFlow, it’s best if you have an understanding of Python. Beginners can learn TensorFlow if they have knowledge of Python already.
If you go in with no understanding of the language, the learning curve will be steeper for you. Ideally, before you start learning TensorFlow, you should ensure you have a grasp of the language.
Understanding Neural Networks
TensorFlow is about deep learning, so ideally, you should have a grasp of the concepts behind neural networks. You won’t need to know everything, but knowing the building blocks of neural networks will work for any beginner. Here are a few concepts you should look into first:
Data Dimensionality And Matrix Algebra
TensorFlow models are fed data as matrices or multidimensional tensors. You’ll need to understand your data’s different dimensions and how they change. Understanding this will make more sense to you when applying data to TensorFlow models.
As part of this, we recommend you brush up on some math too. Consider looking up linear algebra, matrix addition and subtraction, and dot products too.
Layer Types
When you use a network, you’ll find different types of layers. Understanding what these layers do and how they affect data dimensionality can make the learning curve easier.
Cost Functions
Knowing cost functions can help you determine which one is most appropriate for your data.
Activation Functions
Knowing the type of activation function is more appropriate, much like cost functions, is essential. Understand how activation functions work depending on the type of layer and problem you’re working on.
These are the main elements of neural networks that you should consider. Once you have a solid understanding of these foundations, you can learn about more advanced concepts.
Data Preprocessing
As part of your time on TensorFlow, you’ll need to train a model using your own data. Raw data won’t be enough for this, so it’s best to learn how to manipulate and preprocess your data. After all, you can’t just import raw data.
While TensorFlow offers plenty of tools to manipulate and preprocess data, learning how to import external data is a good idea. This will make it easier to transition to preprocessing your data on TensorFlow.
Keras Sequential API
Keras is an application processing interface that simplifies the syntax that TensorFlow uses. While it doesn’t stop you from using raw TensorFlow in your code, it will help you work more quickly. TensorFlow itself is best for functionality, but you should use Keras for ease of use.
Using Keras will be a quicker and easier way to build and train a model, especially if you’re not familiar with data preprocessing yet. Once you’re familiar with Keras Sequential API, consider learning more about functional API, data types, and arithmetic operators.
A functional API is more powerful and will allow you to customize models to a greater extent than simply using a sequential API.
Where To Learn?
If you’re completely new to TensorFlow, it’s easy to become overwhelmed by the amount you will have to learn. To help you, we’ve compiled a list of resources that will help you understand the foundations you should know first. Let’s take a look at where you can gather resources.
Online Courses
Nowadays, accessing online courses related to TensorFlow is easier than ever. You’ll notice there’s a wide range of courses available to choose from, which may make them more difficult to choose from.
All courses online are made by different tutors who have different levels of expertise with TensorFlow. While it may not seem like it’s an issue, we recommend searching for a course based on your judgment of the reviews.
Another factor you should consider when finding an online course that’s right for you is that you should always look for one that you can afford. The good thing about online courses is that you will be led to practical resources to help you learn.
Courses aren’t only theory-based but also offer demonstrations of what you need to do. If you prefer visual aides where you can work alongside your course, then online courses are the best way for you to learn.
YouTube
Likewise, have you considered looking at YouTube for assistance if you can’t afford online courses? Many users have created their own tutorials to help you learn how to use TensorFlow, free of charge. Look on YouTube for any tutorials that may interest you.
They often teach you how they work in a similar way to online courses. However, like with online courses, you should ensure they’re good quality videos with excellent learning material too.
Books
Books are an excellent choice if you need resources that you can flick through when you need them. There are many books that will teach you about Python and machine learning. While books are not a primary tool to teach you, they’re a great resource for material.
Books tend to go more in-depth than online courses as there’s no time limit to them. However, you will need to check that the material is still in date.
TensorFlow Tutorials
Finally, we suggest looking at TensorFlow itself to learn. The TensorFlow team has many guides and tutorials for their users to access on their website. These will make the process even easier for you to learn it.
If you need to learn anything specific, contact TensorFlow directly if you need help. Not only are the guides helpful, but they will also provide documents to view a step-by-step process on how everything works. Learning TensorFlow fast can be difficult, but it’s not impossible.
It can be done with hard work, so don’t be afraid to check external resources to learn more than you need to. Once you learn the fundamentals, you should have no issues moving to more advanced models.
