An introduction to neural networks: AI/ML for beginners

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Last updated on September 30th, 2022 at 08:46 am

The field of AI and machine learning is overgrowing, with new advancements in algorithms happening nearly every day. One area with a lot of growth recently is neural networks, which are artificially intelligent systems built on an architecture inspired by the human brain. In this post, we will explore what precisely neural networks are and how they work so you can get started today!

What is a neural network?

Neural networks are machine learning algorithms that you can use to recognize objects in pictures or understand human speech. 

For example, imagine you wish to teach a convolutional neural network how to recognize pictures of cats. You might show the computer thousands of examples of what cats look like and let it learn from that data. Then, when somebody shows the computer a picture that isn't a cat, it could determine whether or not this is an image of something else using its knowledge of cats.

A step-by-step tutorial on how to train the convolutional neural network and make predictions:

 

  • Choose your dataset:

 

The first step is choosing a dataset to train your neural network. It could be a data set of images, text, or anything else you want to predict.

 

  • Preprocess the data:

 

Before starting training your neural network, you need to preprocess the data. It includes cleaning and formatting the data to be ready to be used by the deep neural network.

 

  • Choose your model:

 

The next step is to choose a model for your neural network. There are many different models, so you need to choose one that will work best for your dataset.

 

  • Train the model:

 

Now it's time to train the network. It is where you will feed in your data and let the neural network learn from it.

The future of AI/ML:

AI/ML is becoming more widely used today. AI/ML has many benefits for the world around us. Machine learning help diagnose diseases, drive cars and even write music!

  • Websites like Amazon use AI/ML to recommend products you may like based on what you have bought in the past.
  • Facebook uses AI/ML to determine which posts or status to show first in your newsfeed.
  • Google uses AI/ML to generate search results.

The possibilities are endless, and the future of AI/ML is inspiring!

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