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Comparison between Deep Learning & Machine Learning

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All of a sudden every one is talking about them – irrespective of whether they understand the differences or not! Whether you have been actively following data science or not – you would have heard these terms. If you have often wondered to yourself what is the difference between machine learning and deep learning, read on to find out a detailed comparison in simple layman language. I have explained each of these term in detail. Then I have gone ahead to compare both of them and explained where we can use them.


Deep Q Learning with Keras and Gym – IIoT & Machine Learning

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This blog post will demonstrate how deep reinforcement learning (deep q learning) can be implemented and applied to play a CartPole game using Keras and Gym, in only 78 lines of code! I'll explain everything without requiring any prerequisite knowledge about reinforcement learning.


Comparison between Deep Learning & Machine Learning

#artificialintelligence

All of a sudden every one is talking about them – irrespective of whether they understand the differences or not! Whether you have been actively following data science or not – you would have heard these terms. If you have often wondered to yourself what is the difference between machine learning and deep learning, read on to find out a detailed comparison in simple layman language. I have explained each of these term in detail. Then I have gone ahead to compare both of them and explained where we can use them. Let us start with the basics – What is Machine Learning and What is Deep Learning.


Unsupervised Feature Learning and Deep Learning Tutorial

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Description: This tutorial will teach you the main ideas of Unsupervised Feature Learning and Deep Learning. By working through it, you will also get to implement several feature learning/deep learning algorithms, get to see them work for yourself, and learn how to apply/adapt these ideas to new problems. This tutorial assumes a basic knowledge of machine learning (specifically, familiarity with the ideas of supervised learning, logistic regression, gradient descent). If you are not familiar with these ideas, we suggest you go to this Machine Learning course and complete sections II, III, IV (up to Logistic Regression) first.


Best and No.1 Introduction to Reinforcement Learning! - WriteX.today

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Let's see some simple example which helps you to illustrate the reinforcement learning mechanism. Consider the scenario of teaching new tricks to your cat. There are three approaches to implement a Reinforcement Learning algorithm. In a value-based Reinforcement Learning method, you should try to maximize a value function V(s). In this method, the agent is expecting a long-term return of the current states under policy π.