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	<title>data mining Archives &#8212; MATLAB Number ONE</title>
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	<description>MATLAB Simulink &#124; Tutorial &#124; Code &#124; Project</description>
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	<title>data mining Archives &#8212; MATLAB Number ONE</title>
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		<title>Kaggle Overview</title>
		<link>https://matlab1.com/kaggle-overview/</link>
					<comments>https://matlab1.com/kaggle-overview/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Sat, 16 Jun 2018 13:08:53 +0000</pubDate>
				<category><![CDATA[data mining]]></category>
		<category><![CDATA[Deep Learning]]></category>
		<guid isPermaLink="false">https://matlab1.com/?p=5636</guid>

					<description><![CDATA[<p>Kaggle is a platform for data sciences developer. It is based on two programming languages, Python and R . It has many outstanding features : You can find and use dataset in your machine learning application. You can find datasets in the link ( https://www.kaggle.com/datasets ) There is many competitions in kaggle. You can join a [&#8230;]</p>
<p>The post <a href="https://matlab1.com/kaggle-overview/">Kaggle Overview</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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		<title>JUPYTER: USING IT AND ITS GREAT FUNCTIONS</title>
		<link>https://matlab1.com/jupyter-using-it-and-its-great-functions/</link>
					<comments>https://matlab1.com/jupyter-using-it-and-its-great-functions/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Tue, 12 Jun 2018 13:02:00 +0000</pubDate>
				<category><![CDATA[data mining]]></category>
		<category><![CDATA[Deep Learning]]></category>
		<guid isPermaLink="false">https://matlab1.com/?p=5611</guid>

					<description><![CDATA[<p>The Jupyter notebook is a great friend of the data scientist. It allows the user to write code and create visualizations of data all in the same tab on their browser. It is included in the standard distribution of Anaconda, and can be launched from the command line (note, not inside Python, but in the terminal window) [&#8230;]</p>
<p>The post <a href="https://matlab1.com/jupyter-using-it-and-its-great-functions/">JUPYTER: USING IT AND ITS GREAT FUNCTIONS</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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		<title>THE BIGGEST DIFFERENCES BETWEEN PYTHON 2 AND 3</title>
		<link>https://matlab1.com/the-biggest-differences-between-python-2-and-3/</link>
					<comments>https://matlab1.com/the-biggest-differences-between-python-2-and-3/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Tue, 12 Jun 2018 12:51:22 +0000</pubDate>
				<category><![CDATA[data mining]]></category>
		<category><![CDATA[Deep Learning]]></category>
		<guid isPermaLink="false">https://matlab1.com/?p=5609</guid>

					<description><![CDATA[<p>1. Division. Python 3 does floating point division between two integers if you specify the division with two slashes (//). However, if we want Python 2 to do floating point division by default , we can use the handy function: &#62;&#62; from__future__ import division &#62;&#62;&#62; 3/2 1.5 2. Printing. In Python 3, you have to [&#8230;]</p>
<p>The post <a href="https://matlab1.com/the-biggest-differences-between-python-2-and-3/">THE BIGGEST DIFFERENCES BETWEEN PYTHON 2 AND 3</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
]]></description>
		
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		<title>Data science interview preparation checklist:</title>
		<link>https://matlab1.com/data-science-interview-preparation-checklist/</link>
					<comments>https://matlab1.com/data-science-interview-preparation-checklist/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Tue, 12 Jun 2018 12:11:52 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[data mining]]></category>
		<category><![CDATA[Deep Learning]]></category>
		<guid isPermaLink="false">https://matlab1.com/?p=5600</guid>

					<description><![CDATA[<p>1. Study the company 2. Understand how the company makes money 3. Dress slightly above how you expect the company dresses 4. Practice interviewing (have someone else quiz you) and be able to answer why you would be a good fit at that company 5. Have questions ready for the interviewer 6. Practice a 2-minute description [&#8230;]</p>
<p>The post <a href="https://matlab1.com/data-science-interview-preparation-checklist/">Data science interview preparation checklist:</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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		<title>One-hot encoding</title>
		<link>https://matlab1.com/one-hot-encoding/</link>
					<comments>https://matlab1.com/one-hot-encoding/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Tue, 05 Jun 2018 07:56:25 +0000</pubDate>
				<category><![CDATA[data mining]]></category>
		<category><![CDATA[Deep Learning]]></category>
		<guid isPermaLink="false">https://matlab1.com/?p=5477</guid>

					<description><![CDATA[<p>One-hot encoding is a way to represent the target variables or classes in case of a classification problem. The target variables can be converted from the string labels to one-hot encoded vectors. A one-hot vector is filled with 1 at the index of the target class but with 0 everywhere else. For example, if the target classes are cat [&#8230;]</p>
<p>The post <a href="https://matlab1.com/one-hot-encoding/">One-hot encoding</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
]]></description>
		
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		<title>Aircraft Dynamics</title>
		<link>https://matlab1.com/aircraft-dynamics/</link>
					<comments>https://matlab1.com/aircraft-dynamics/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Wed, 29 Nov 2017 18:00:00 +0000</pubDate>
				<category><![CDATA[data mining]]></category>
		<category><![CDATA[10257012]]></category>
		<category><![CDATA[Aircraft]]></category>
		<category><![CDATA[Aircraft Dynamics]]></category>
		<category><![CDATA[Dynamics]]></category>
		<guid isPermaLink="false">https://matlab1.com/?p=3937</guid>

					<description><![CDATA[<p>Aircraft Dynamics &#160; &#160;</p>
<p>The post <a href="https://matlab1.com/aircraft-dynamics/">Aircraft Dynamics</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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		<title>Modbus</title>
		<link>https://matlab1.com/modbus/</link>
					<comments>https://matlab1.com/modbus/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Wed, 29 Nov 2017 17:06:34 +0000</pubDate>
				<category><![CDATA[data mining]]></category>
		<category><![CDATA[10256548]]></category>
		<category><![CDATA[Modbus]]></category>
		<category><![CDATA[programmable logic controllers]]></category>
		<guid isPermaLink="false">https://matlab1.com/?p=3907</guid>

					<description><![CDATA[<p>Modbus MODBUS was established in the late 1970’s as a protocol to be used with programmable logic controllers PLCs by Modicon. It works on RS-485 serial communications and due to its differential signaling it reduces errors in communication. There are several versions of the MODBUS protocol. From MODBUS RTU to MODBUS ASCII and MODBUS TCP, they [&#8230;]</p>
<p>The post <a href="https://matlab1.com/modbus/">Modbus</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
]]></description>
		
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		<item>
		<title>Multi-Agent Systems</title>
		<link>https://matlab1.com/multi-agent-systems/</link>
					<comments>https://matlab1.com/multi-agent-systems/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Tue, 28 Nov 2017 17:41:41 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[data mining]]></category>
		<category><![CDATA[10254716]]></category>
		<category><![CDATA[Deterministic]]></category>
		<category><![CDATA[Intelligent Agents Architectures]]></category>
		<category><![CDATA[Multi-Agent Systems]]></category>
		<category><![CDATA[non-deterministic]]></category>
		<guid isPermaLink="false">https://matlab1.com/?p=3841</guid>

					<description><![CDATA[<p>Multi-Agent Systems Basically, an agent is a computer system which can decide to take an action in order to satisfy designed objectives. Agents that must operate robustly in rapidly changing, unpredictable, or open environments, where there is a significant possibility that actions can fail are known as intelligent agents, or sometimes autonomous agents .Figure 4.1 [&#8230;]</p>
<p>The post <a href="https://matlab1.com/multi-agent-systems/">Multi-Agent Systems</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
]]></description>
		
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		<title>Artificial Neural Network Design and Implementation</title>
		<link>https://matlab1.com/artificial-neural-network-design-implementation/</link>
					<comments>https://matlab1.com/artificial-neural-network-design-implementation/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Tue, 28 Nov 2017 17:18:18 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[data mining]]></category>
		<category><![CDATA[10254716]]></category>
		<category><![CDATA[Backpropagation (BP)]]></category>
		<category><![CDATA[feed-forward neural network (FFNN)]]></category>
		<category><![CDATA[Least Mean Square (LMS)]]></category>
		<category><![CDATA[Levenberg-Marquardt Backpropagation Algorithm]]></category>
		<guid isPermaLink="false">https://matlab1.com/?p=3785</guid>

					<description><![CDATA[<p>Neural network structure and model In this work, a multi-layer feed-forward neural network (FFNN) is proposed as shown in Figures 3.1 and 3.2. The Levenberg-Marquardt Back Propagation (LMBP) method is selected for training the ANN network to increase convergence speed, and to avoid long training times. The LMBP algorithm is based on numerical optimization techniques [&#8230;]</p>
<p>The post <a href="https://matlab1.com/artificial-neural-network-design-implementation/">Artificial Neural Network Design and Implementation</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
]]></description>
		
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		<title>Rotary optical encoders</title>
		<link>https://matlab1.com/rotary-optical-encoders/</link>
					<comments>https://matlab1.com/rotary-optical-encoders/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Tue, 28 Nov 2017 15:53:32 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[data mining]]></category>
		<category><![CDATA[10254716]]></category>
		<category><![CDATA[electromechanical device]]></category>
		<category><![CDATA[Encoder measurement]]></category>
		<category><![CDATA[light-emitting diode (LED)]]></category>
		<category><![CDATA[Quadrature Encoder]]></category>
		<category><![CDATA[Rotary optical encoders]]></category>
		<guid isPermaLink="false">https://matlab1.com/?p=3774</guid>

					<description><![CDATA[<p>Rotary optical encoders optical encoders Encoder is defined as an electromechanical device that measures motion or position. Encoders typically use optical sensors to generate electrical pulse train signals which are converted to position, motion, or direction . Figure 2.16 shows the main components of a rotary encoder including a disk, a light-emitting diode (LED), and [&#8230;]</p>
<p>The post <a href="https://matlab1.com/rotary-optical-encoders/">Rotary optical encoders</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
]]></description>
		
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