{"id":246278,"date":"2022-01-01T09:13:32","date_gmt":"2022-01-01T09:13:32","guid":{"rendered":"https:\/\/imarticus.org\/?p=246278"},"modified":"2022-09-30T08:46:52","modified_gmt":"2022-09-30T08:46:52","slug":"an-introduction-to-neural-networks-ai-ml-for-beginners","status":"publish","type":"post","link":"https:\/\/imarticus.org\/blog\/an-introduction-to-neural-networks-ai-ml-for-beginners\/","title":{"rendered":"An introduction to neural networks: AI\/ML for beginners"},"content":{"rendered":"

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<\/a><\/strong> are and how they work so you can get started today!<\/span><\/p>\n

What is a neural network?<\/b><\/h2>\n

Neural networks are machine learning algorithms that you can use to recognize objects in pictures or understand human speech.\u00a0<\/span><\/p>\n

For example, imagine you wish to teach a <\/span>convolutional<\/span> 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.<\/span><\/p>\n

A step-by-step tutorial on how to train the convolutional neural network and make predictions:<\/b><\/h2>\n

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