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• 15:13, 8 May 2024 Rice talk contribs created page Dynamic discipline (Created page with "Synchronous sequential circuit inputs must be stable during aperture time around clock edge. Category:Computer Architecture")
• 22:22, 6 May 2024 Rice talk contribs created page D latch (Created page with "thumb|Figure 1. Schematic of a D latch The '''D latch''' is a direct upgrade from an SR latch. It has two inputs: (D)ata and (E)nabler. When ''E'' is activated, ''D'' is stored into the latch. When the enabler is deactivated, the circuit continues to latch the current value regardless of ''D''. = Clocked D latch = By connecting a clock to the enabler, you get a '''clocked D latch''' that is synchronized with the rest of the circuit. This is...") Tag: Visual edit
• 22:21, 6 May 2024 Rice talk contribs created page File:D latch.png
• 22:21, 6 May 2024 Rice talk contribs uploaded File:D latch.png
• 20:21, 6 May 2024 Rice talk contribs created page File:SR latch with not.png
• 20:21, 6 May 2024 Rice talk contribs uploaded File:SR latch with not.png
• 20:12, 6 May 2024 Rice talk contribs created page File:SR latch schematic.png
• 20:12, 6 May 2024 Rice talk contribs uploaded File:SR latch schematic.png
• 19:35, 3 May 2024 Rice talk contribs created page Timer (Created page with "A '''timer''' is a circuit that takes in an increase in input and generates an increase in output after an amount of time passes. = Real timers = Ideally, we want an instant transition from low to high. This is impossible. Real world timers looks kinda like a sigmoid lol. Category:Computer Architecture")
• 19:34, 3 May 2024 Rice talk contribs created page Finite state machine (Created page with "The '''state''' of the program is its memory. A '''finite state machine''' continuously computes the current state with the previous state based on a function. In a '''Moore circuit''', output only depends on the current state. In contrast, in a ''Mealy circuit''', input is also wired into the output logic. Category:Computer Architecture")
• 15:21, 3 May 2024 Rice talk contribs created page Timing (Created page with " = Delay = The amount of time passed before the output follows the input is the propagation delay. It is the maximum delay from input to output. During this time, the output is unpredictable. Since the output is unpredictable during the time after input and before propagation delay passed, it is possible to read an output during this time. This is the contamination delay: the minimum delay from input to output. The reason for the unpredictability at contaminati...")
• 15:09, 3 May 2024 Rice talk contribs created page Propagation delay (Created page with "The propagation delay is the time before which a circuit element stabilizes. Category:Computer Architecture")
• 21:28, 1 May 2024 Rice talk contribs created page Linear combination (Created page with "The linear combination of any homogeneous solution is still a solution. Category:Differential Equations")
• 21:27, 1 May 2024 Rice talk contribs created page Second order linear ODE (Created page with "Second order linear ODEs are in the following form: <math> y''+p(t)y'+q(t)y=g(t) </math> Important types of second order linear ODEs include * Homogeneous * Constant coefficients (where p and q are constants) = Initial value problem = There are two arbitrary constants in the solution of a second order linear ODE, so we need two initial conditions. <math> \begin{cases} y(t_0)=y_0\\ y'(t_0)=y_0' \end{cases} </math> = Solutions = == Constant coefficient, homogeneou...")
• 21:21, 1 May 2024 Rice talk contribs moved page First Order Scalar ODE to First order scalar ODE
• 03:48, 1 May 2024 Rice talk contribs created page Nondimensionalization (Created page with "'''Nondimensionalization''' is a technique for simplifying equations, where the dependent variables are changed in such a way that constants are removed. An example would be logistic ODE.")
• 03:47, 1 May 2024 Rice talk contribs created page Logistic ODE (Created page with "Solved by nondimensionalization Category:Differential Equations")
• 03:22, 1 May 2024 Rice talk contribs created page Feed-forward pass (Created page with "The '''feed-forward pass''' is the process of obtaining the result of a neural network. The input is fed into the network, which transforms it layer-by-layer, each layer ''feeding'' its computed results ''forward'' to the next layer until the output layer is reached.") Tag: Visual edit
• 03:18, 1 May 2024 Rice talk contribs created page Back propagation (Created page with "'''Back propagation''' is a error calculation technique. It consists of passing a loss function ''backwards'' through a neural network layer-by-layer to update its weights. = Procedure = Consider the following RSS loss function (halved for easier derivative). <math> E = \frac{1}{2}\sum (y_i - \bf{w}\bf{x})^2 </math> After each feed-forward pass where one data point is passed through the neural network, the gradient of the loss function is computed. We compute gra...")
• 00:22, 1 May 2024 Rice talk contribs created page Label encoding (Created page with "'''Label encoding''' encodes ordinal categorical data into numerical ones by representing them as discrete numbers. It does not work for nominal data. Category: Machine Learning")
• 00:21, 1 May 2024 Rice talk contribs created page One-hot encoding (Created page with "'''One-hot encoding''' encodes nominal categorical data into numerical ones by representing them as binary vectors. Category: Machine Learning")
• 00:15, 1 May 2024 Rice talk contribs created page Activation function (Created page with "The '''activation function''' determines the output of a neuron in a neural network. It generates the output of the neuron from the linear combination of inputs calculated by the neuron. The choice of activation function varies depending on the machine learning task. A simple linear activation function or no activation function is just linear regression. A sigmoid function can be used for a classification task.")
• 00:14, 1 May 2024 Rice talk contribs moved page Linear Regression to Linear regression
• 23:50, 30 April 2024 Rice talk contribs created page Neural network (Created page with "A '''neural network''' is a type of machine learning model that utilizes layers of connected '''neurons''' to perform classification and regression. = Structure = == Neuron == The '''neuron''' is the data-processing unit that composes a neural network. It combines information from multiple neurons (or input) and become activated or deactivated. The output is determined by the following steps: # A neuron generates a linear combination of input data, ''z''. This is done...")
• 23:31, 30 April 2024 Rice talk contribs created page File:Covex vs. Non-convex.png
• 23:31, 30 April 2024 Rice talk contribs uploaded File:Covex vs. Non-convex.png
• 23:30, 30 April 2024 Rice talk contribs created page Artificial neural network (Created page with "An '''artificial neural network (ANN)''' is a machine learning algorithm that uses three layers of neurons to perform classification/regression. = Structure = All ANN's consist of three layers of neurons: the input layer, the hidden layer, and the output layer. The number of neurons in each layer determines the complexity of the model, with a larger layer indicating a more complicated model. Each neuron takes in information from neurons of the previous layer (and for t...")
• 15:35, 29 April 2024 Rice talk contribs created page SR latch (Created page with "thumb|Figure 1. SR latch circuit and truth table The '''set-reset latch''' is a circuit that stores a value in a bistable circuit using two NOR gates. It is the fundamental building block for memory cells.") Tag: Visual edit
• 15:34, 29 April 2024 Rice talk contribs created page File:SR Latch.png
• 15:34, 29 April 2024 Rice talk contribs uploaded File:SR Latch.png
• 15:18, 29 April 2024 Rice talk contribs created page Astable (Created page with "'''Astable''' circuits do not have a stable state. An example would be a clock, which fluctuates between 0 and 1. Category:Computer Architecture") Tag: Visual edit
• 15:17, 29 April 2024 Rice talk contribs created page Bistable (Created page with "A '''bistable''' circuit has two stable states. Think of two NOT gates feedbacking in a loop. Category:Computer Architecture") Tag: Visual edit
• 22:27, 26 April 2024 Rice talk contribs created page Existence-uniqueness (Created page with "Consider an IVP for a general first order scalar ODE. <math> \begin{cases} y' = f(t,y)\\ y(t_0) = y_0 \end{cases} </math> The '''existence-uniqueness theorem''' theorem states that if <math>f(t,y)</math> and its derivative w.r.t. y is continuous in some rectangle <math>a<t<b</math>, <math>c<y<d</math> about <math>(t_0, y_0)</math>, then there exists a unique solution of the IVP defined for some time interval <math>a'<t<b'</math> about...")
• 06:47, 26 April 2024 Rice talk contribs moved page Outliers to Outlier
• 06:45, 26 April 2024 Rice talk contribs created page File:Skewness mitigation.png
• 06:45, 26 April 2024 Rice talk contribs uploaded File:Skewness mitigation.png
• 06:44, 26 April 2024 Rice talk contribs created page Skewness (Created page with "The '''skewness''' of a dataset determines the direction of the outliers. = Impact = Many models assume the data to be normally distributed. Skewed data in those models will result in inaccurate predictions. = Detection = Data skewness is detected during Exploratory data analysis. The first method is visualization. Just look at a graph lol. Numerically, in a dataset, if the median < the mean, then it is skewed to the right. Vice versa. = Mitigate pr...")
• 06:40, 26 April 2024 Rice talk contribs created page Outliers (Created page with "Outliers are samples that show abnormal distance from other samples. They impact the accuracy of the model. Outliers are detected during Exploratory data analysis. Several detection methods are listed. *Background knowledge such as impossible values like negative age *Visualization such as scatter plot *Data Analysis such as box plot *ML algorithms such as One-Class-SVM Category:Machine Learning")
• 06:22, 26 April 2024 Rice talk contribs created page Dataset (Created page with "In machine learning, a model operates on a '''dataset'''. = Attributes of a dataset = The '''completeness''' of a dataset is the extent to which it contains all relevant '''features''' necessary for a given task. A dataset needs to have a sufficient number of observations, measured by the '''size''' of the dataset. The '''validity''' of the dataset is how accurate, clean, and relevant the data in the dataset is. A dataset can be '''high dimensional''', meaning that i...")
• 06:12, 26 April 2024 Rice talk contribs moved page Exploratory Data Analysis to Exploratory data analysis
• 05:26, 26 April 2024 Rice talk contribs created page File:Linearly separable data.png
• 05:26, 26 April 2024 Rice talk contribs uploaded File:Linearly separable data.png
• 05:25, 26 April 2024 Rice talk contribs created page Perceptron learning (Created page with "'''Perceptron learning''' is good for classifying ''linearly separable data'', as seen in figure 1. Category:Machine Learning")
• 05:24, 26 April 2024 Rice talk contribs created page Newton's method (Created page with "'''Newton's method''' is an alternative to Gradient Descent. In contrast to GD, which uses the first derivative to approach the optimal model, Newton's method adds the ''second derivative'' to converge ''faster''. Newton's method has the drawback of being more computationally expensive due to the need to find the second derivative. <math> w_j = w_j - a\frac{\frac{\partial l}{\partial w_j}}{\frac{\partial^2 l}{\partial w_j^2}} </math> Category:Machine Learning")
• 01:19, 26 April 2024 Rice talk contribs created page File:Logistic regression sigmoid.png
• 01:19, 26 April 2024 Rice talk contribs uploaded File:Logistic regression sigmoid.png
• 01:08, 26 April 2024 Rice talk contribs created page Logistic regression (Created page with "= Linear regression = Linear regression cannot be directly used for (binary) classification. Indirectly, a threshold is used. When the value is above the threshold, it is considered 1; when it is below, it is considered 0. Classification using linear regression is sensitive to the threshold. The problem with this approach is the difficulty in determining a good threshold.")
• 01:02, 26 April 2024 Rice talk contribs created page Binary classification (Created page with "'''Binary classification''' algorithms classify data into two categories. Detecting the presence of a trait is a common application. = Algorithms = * Logistic regression * Perceptron learning Category:Machine Learning")
• 23:41, 23 April 2024 Rice talk contribs created page Homogeneous (Created page with "In differential equations, homogeneous ODEs have RHS be 0 in standard form. Category:Differential Equations") Tag: Visual edit
• 23:25, 23 April 2024 Rice talk contribs moved page Integrating factors to Integrating factor