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Artificial Neural Networks IT Powerpoint Presentation Slides

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Deliver this complete deck to your team members and other collaborators. Encompassed with stylized slides presenting various concepts, this Artificial Neural Networks IT Powerpoint Presentation Slides is the best tool you can utilize. Personalize its content and graphics to make it unique and thought-provoking. All the fifty three slides are editable and modifiable, so feel free to adjust them to your business setting. The font, color, and other components also come in an editable format making this PPT design the best choice for your next presentation. So, download now.

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  • IT , Artificial Intelligence

Content of this Powerpoint Presentation

Slide 1: This slide introduces Artificial Neural Networks (IT). State your company name and begin.
Slide 2: This slide states Agenda of the presentation.
Slide 3: This slide presents Table of Content for the presentation.
Slide 4: This slide highlights title for topics that are to be covered next in the template.
Slide 5: This slide shows About our artificial neural network learning institute.
Slide 6: This slide presents Education required to learn artificial neural networking.
Slide 7: This slide highlights title for topics that are to be covered next in the template.
Slide 8: This slide displays Introduction to artificial neural network.
Slide 9: This slide represents Advantages of artificial neural network.
Slide 10: This slide highlights title for topics that are to be covered next in the template.
Slide 11: This slide showcases Architecture of Artificial Neural Network.
Slide 12: This slide shows Layers of artificial neural network(ann) architecture.
Slide 13: This slide presents Working of artificial neural network.
Slide 14: This is another slide continuing Working of artificial neural network.
Slide 15: This slide highlights title for topics that are to be covered next in the template.
Slide 16: This slide displays Introduction to artificial neuron.
Slide 17: This slide represents Overview of activation function.
Slide 18: This slide showcases Two types of activation function.
Slide 19: This slide shows Different types of non-linear activation functions.
Slide 20: This slide presents Sigmoid non-linear activation function.
Slide 21: This slide displays Hyperbolic tangent(Tanh) activation function.
Slide 22: This slide represents ReLU (Rectified Linear Unit) activation function.
Slide 23: This slide highlights title for topics that are to be covered next in the template.
Slide 24: This slide shows feedforward, one of the types of Artificial Neural Networks(ANN).
Slide 25: This slide depicts the feedback network, which is the other type of ANN.
Slide 26: This slide highlights title for topics that are to be covered next in the template.
Slide 27: This slide presents Overview of cost function in ANN.
Slide 28: This slide displays Two processes for minimizing cost function.
Slide 29: This slide highlights title for topics that are to be covered next in the template.
Slide 30: This slide represents Applications of artificial neural networks.
Slide 31: This slide showcases Use cases of artificial neural network.
Slide 32: This slide highlights title for topics that are to be covered next in the template.
Slide 33: This slide shows Artificial neural network learning techniques.
Slide 34: This slide highlights title for topics that are to be covered next in the template.
Slide 35: This slide presents Disadvantages of artificial neural networks.
Slide 36: This slide highlights title for topics that are to be covered next in the template.
Slide 37: This slide displays Training schedule for artificial neural network.
Slide 38: This slide represents Course fee for artificial neural network.
Slide 39: This slide highlights title for topics that are to be covered next in the template.
Slide 40: This slide showcases 30-60-90 days plan for ANN course.
Slide 41: This slide highlights title for topics that are to be covered next in the template.
Slide 42: This slide shows Roadmap for ANN learning course.
Slide 43: This slide contains all the icons used in this presentation.
Slide 44: This slide is titled as Additional Slides for moving forward.
Slide 45: This slide contains Puzzle with related icons and text.
Slide 46: This slide depicts Venn diagram with text boxes.
Slide 47: This is Our Target slide. State your targets here.
Slide 48: This slide shows Post It Notes. Post your important notes here.
Slide 49: This slide provides Clustered bar chart with two products comparison.
Slide 50: This slide showcases Magnifying Glass to highlight information, specifications, etc.
Slide 51: This is a Timeline slide. Show data related to time intervals here.
Slide 52: This is a Comparison slide to state comparison between commodities, entities etc.
Slide 53: This is a Thank You slide with address, contact numbers and email address.

FAQs

An artificial neural network (ANN) is a computational model inspired by the structure and function of the human brain. It consists of interconnected nodes or neurons that process and transmit information.

Some advantages of using artificial neural networks include their ability to learn and adapt, their ability to work with complex and nonlinear data, and their potential for high accuracy in prediction and classification tasks.

There are several types of activation functions used in artificial neural networks, including sigmoid, hyperbolic tangent (Tanh), and rectified linear unit (ReLU).

The two types of artificial neural networks are feedforward networks and feedback networks. Feedforward networks propagate information in a single direction from input to output, while feedback networks allow information to flow in both directions.

Artificial neural networks have a wide range of applications, including image and speech recognition, natural language processing, predictive maintenance, financial forecasting, and medical diagnosis.

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    by Delmer Black

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