Ppt for machine learning.Machine Learning Infographics | Google Slides & PowerPoint

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Tags White Infographics Flat Infographics. Related presentations. Download Premium template Unlock this template and gain unlimited access. Go Premium Are you already Premium? Sign in for free. Infographics Download Download Premium template Go Premium. This type of algorithm consists of input data without labelled response. There will not be any pre existing labels and human intervention is also less. It is mostly used in exploratory analysis as it can automatically identify the structure in data.

This model is used in making a sequence of decisions. It is an learning by interacting with the environment. It is based on the observation that intelligent agents tend to repeat the action that are rewarded for and refrain from action that are punished for. It can be said that it is an trail and error method in finding the best outcome based on experience.

Slide 32 : This slide is curated to address all the critical questions with regards to the concept of Deep Learning like what is deep learning, deep learning process, classification of neural networks, types of deep learning networks, feed-forward neural networks, recurrent neural networks, convolutional neural networks, reinforcement learning, examples of deep learning applications, why is deep learning important, and limitations of deep learning.

Slide 34 : This slide gives you a glimpse of the complex Deep Learning Process which includes understanding the problem, identifying data, selecting deep learning algorithms, training the model, and testing the model.

Slide 37 : This slide elaborates on the Feed-forward Neural Networks and their input layer, hidden layer, and output layer. Slide 38 : This slide elucidates the Recurrent Neural Networks thoroughly. Slide 39 : This slide gives a detailed explanation of the Convolutional Neural Networks.

Slide 40 : This slide explains how Reinforcement Learning goes on to maximize the rewards. Slide 46 : This slide provides you detailed information about Artificial Intelligence.

Slide 47 : The current slide gives you an introduction to the Machine Learning and how it learns, predicts, and improves the ordinary system. Slide 48 : This slide will take you through the concept of Deep Learning in detail. Slide 51 : The purpose of this slide is to highlight the difference between Machine Learning and Deep Learning. Slide 53 : This slide titled Supervised Machine Learning focuses on explaining the concept by addressing questions like types of machine learning, what is supervised machine learning, gow supervised learning works, types of supervised machine learning algorithms, supervised vs unsupervised learning techniques, advantages of supervised learning, and disadvantages of supervised learning.

Slide 54 : The following slide provides you with various types of Machine Learning like supervised learning, unsupervised learning, and reinforcement learning.

Slide 56 : This slide mentions the mechanism of How Supervised Machine Learning works and all the steps it entails like classification and regression. Slide 57 : This slide brings various Types of Supervised Machine Learning Algorithms to the fore like classification that includes fraud detection, email spam detection, diagnostics, and image classification.

Also, regression, that includes risk assessment and score prediction. Slide 58 : This slide calls attention to Supervised classification, regression vs. Unsupervised Machine Learning Techniques clustering, association. Slide 59 : This slide emphasizes the Advantages of Supervised Learning. Slide 60 : This slide argues about the Disadvantages of Supervised Learning. Slide 61 : This slide addresses the concept of Unsupervised Machine Learning and the questions associated with it like what is unsupervised machine learning, how unsupervised machine learning works, types of unsupervised learning, and disadvantages of unsupervised learning.

Slide 62 : This slide focuses on What Unsupervised Learning is and its input data, algorithms as well as output. Slide 63 : This slide underlines How Unsupervised Machine Learning works and the problems it solves like clustering and anomaly detection. Slide 64 : This slide explores the various Types of Unsupervised Learning such as dimensionality reduction and clustering.

Slide 65 : The following slide displays the Disadvantages of Unsupervised Learning. Slide 66 : This slide is titled reinforcement learning and it highlights the questions related to the concept like what is reinforcement learning, how reinforcement learning works, types of reinforcement learning, advantages, and disadvantages of reinforcement learning. Slide 67 : This slide highlights the concept of Reinforcement Learning and its key steps like input, response, feedback, learning, and reinforcement response.

Slide 68 : This slide elaborates on the functioning of Reinforcement Learning and the environment as well as the agent it deals with. Supervised learning Unsupervised learning Semi-supervised learning Unsupervised learning Contd. Application Furthermore, there are more and more techniques apply machine learning as a solution.

In the future, machine learning will play an important role in our daily life. Conclusion You just clipped your first slide! Clipping is a handy way to collect important slides you want to go back to later. Now customize the name of a clipboard to store your clips. Visibility Others can see my Clipboard. Cancel Save. Get SlideShare without ads Enjoy access to millions of presentations, documents, ebooks, audiobooks, magazines, and more ad-free.

Read free for 60 days. NipulPatel20 Dec. VedantiKangane Dec. TirthLoliyani Dec. PriyaRani Nov. Show More. Total views. Unlimited Reading Learn faster and smarter from top experts. Unlimited Downloading Download to take your learnings offline and on the go.


 
 

 

Ppt for machine learning.Introduction to Machine learning

 
Slide 22 : This next slide defines the key seven Steps of Machine Learning that are gathering data, choosing a model, preparing the data, evaluation, prediction, hyperparameter tuning, training. It appears that you have an ad-blocker running. Unlock this template and gain unlimited access. Slide 23 : This slide draws a comparison between machine learning and traditional programming. Slide 53 : This slide titled Supervised Machine Learning focuses on explaining the concept by addressing questions like types of machine learning, what is supervised machine learning, gow supervised learning works, types of supervised machine learning algorithms, supervised vs unsupervised learning techniques, advantages of supervised learning, and disadvantages of supervised learning. Download this presentation. Unlimited Downloading Download to take your learnings offline and on the go.❿
 
 

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