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AI Tutorial for Beginners | Artificial Intelligence Course | AI Course for Beginners | What is AI?

🔥1000+ Free Courses With Free Certificates: https://www.mygreatlearning.com/acade... 🔥Build a successful career in Artificial Intelligence and Machine Learning https://www.mygreatlearning.com/pg-pr... AI Tutorial for Beginners | Artificial Intelligence Course | AI Course for Beginners | What is AI? Artificial intelligence (AI), which stands for systems or machines that resemble human intelligence to complete tasks and can iteratively improve themselves based on the information they acquire, is most commonly used to describe such systems or machines. Hello and welcome to the AI tutorial for beginners powered by Great Learning. In this video, we will walk you through the introduction to Artificial Intelligence (AI), which covers the subdomains of AI, the Idea behind neural networks & how AI is applied to the fields of Natural Language Processing and Computer vision, Concepts of Artificial Neural networks & Deep Neural Network, etc. Learning Objectives: Broad Understanding of What AI is Applications of AI Topics Covered: 00:01:09 - What is AI? 00:21:50 - Neural Networks 00:29:21 - Biological Neuron 00:40:43 - Deep Neural Networks 00:43:47 - Natural Language Processing (NLP) 00:49:40 - NLP Use Cases 00:54:56 - Computer Vision 01:00:22 - Convolutional Neural Networks (CNN) 01:02:21 - Computer Vision Use Cases (Facial Recognition) 01:02:21 - Computer Vision Use Cases (Video & Traffic Analytics) What is AI? Scientifically, Artificial Intelligence can be thought as a set of algorithms that can obtain an understanding of data and perform tasks without being explicitly programmed on how to do so. Although modern-day AI has mostly been able to accomplish such results only in narrow, specific domains, the implications of such algorithms if they were able to generalize to a broader form of understanding are quite profound. This has led to the notion of AI as a potentially human-like figure that can think and act on its own very independently, but the reality is that we are very from achieving that level of general intelligence with modern AI Systems. Expert Systems vs Machine Learning One of the ways to understand the scope of AI is to deep dive into various subdomains that utilize AI techniques, and understand how these are applied in various industrial fields. Neural Networks: Neural Networks are the tool of choice for AI algorithms powered by Deep Learning. Neural networks specialize in predictions on unstructured datasets, where they detect non-linear patterns most commonly found in real-world problem statements. The mathematical structure of neural networks, with the input Layer (i/p), Hidden Layer(s), and Output Layer (o/p) along with the combination of linear functions and non-linear activation functions, is what allows neural networks to understand the complex. Non-linear patterns that traditional machine learning algorithms have historically struggled with in the realm of artificial intelligence. Natural Language Processing (NLP): Natural language processing is a field of study that involves the automation of the processes of reading, interpreting, and analyzing natural language by a machine. It includes the application of techniques such as computational linguistics and more recently machine learning, to build real-world applications that work with natural language Machine learning-based NLP is an extremely attractive proposition, due to the sheer amount of unstructured natural language data being generated with every passing year NLP Professionals who can leverage AI techniques are in high demand in the workforce, because underneath this unstructured data lies a lot of actionable information that can help organizations grow and succeed in the marketplace Computer Vision (CV) Can be an overarching term. Some of the tasks that fall under its purview are: 1. Image classification: Labeling an image based on the object in the Image 2. Object Detection & Localization: Detecting an object and localizing it using an abounding box 3. Segmentation: Clustering together parts of the image that belongs to the same object class 4. Image Captioning: Describing the image using natural language processing 5. Generative Modelling: Generating images based on the style of another image 6. Video Analysis: Processing the entire set of image frames for object detection & tracking #artificialintelligence #ai #neuralnetwork #neuralnetworks #machinelearning SOCIAL MEDIA LINKS: 🔹 For more interesting tutorials, don't forget to subscribe to our channel: https://glacad.me/YTsubscribe 🔹 For more updates on courses and tips follow us on: ✅ Telegram: https://t.me/GreatLearningAcademy ✅ Facebook:   / greatlearningofficial