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Software & Coding Articles
Page 54 of 83
How can Deep Learning be used for facial recognition in Machine Learning?
Face recognition is the task of identifying and verifying people present in a photograph based on their face. This is a trivial task for humans, even if the lights are varying or when faces change due to age or they are obstructed with accessories, facial hair and so on.But it remained a fairly challenging computer vision problem until a few years back. Deep learning methods have been able to leverage large datasets of faces and learn various representations of faces, thereby allowing modern learning models to perform well and better.Facial recognition may be used to identify person in a photograph ...
Read MoreWhat are layers in a Neural Network with respect to Deep Learning in Machine Learning?
A neural network can contains any number of neurons. These neurons are organized in the form of interconnected layers. The input layer can be used to represent the dataset and the initial conditions on the data.For example, suppose the input is a grayscale image, the output of every neuron in the input layer would be the intensity of every pixel of the image.This is the reason we don’t count the input layer as a part of the other layers in the neural network. When we refer to a 1-layer net, we actually refer to a simple network that contains one ...
Read MoreExplain what a neuron is, in terms of Neural Network in Machine Learning.
A neuron is a mathematical function that takes one or more values as input and outputs a ingle numerical value −It can be defined as follows −Here, ‘f’ refers to the function.We first computed the weighted sum of the inputs xi and the weights wiThe weight wi is also known as the activation value or activation function.The input xi can be a numerical value that represents the input data or it can be an output from other neurons if the neuron belong to a neural network.The weight wi is a numerical value that can be used to represent the strength ...
Read MoreWhat is a Neural Network in Machine Learning?
A neural network can be understood as a network of hidden layers, an input layer and an output layer that tries to mimic the working of a human brain.The hidden layers can be visualized as an abstract representation of the input data itself. These layers help the neural network understand various features of the data with the help of its own internal logic.These neural networks are non-interpretable models. Non-interpretable models are those which can’t be interpreted or understood even if we observe the hidden layers. This is because the neural networks have an internal logic working on its own, that ...
Read MoreWhat is a Perceptron? What are its limitations? How can these limitations be overcome in Machine Learning?
The basic example of a neural network is a ‘perceptron’. It was invented by Frank Rosenblatt in 1957. The perceptron is a classification algorithm similar to logistic regression. This because, similar to logistic regression, a perceptron has weights, w, and an output function, ‘f’, which is a dot product of the weights and the input.The only difference is that ‘f’ is a simple step function, where a logistic regression rule is applied to the output of the logistic function. On the other hand, perceptron can be understood as an example of a simple one-layer neural feedforward network.The perceptron was considered ...
Read MoreWhy are Neural Networks needed in Machine Learning?
Neural networks have been around for many years, through which they have been praised as well as criticised for their characteristics.But off late, they have gained attention over other machine learning algorithms. Of course, Machine learning algorithms are important as they help achieve certain goals. But what should we do when machine learning algorithms can’t achieve higher accuracy?This is where deep learning algorithms come into play. They mimic the layers of the human brain, and try to take optimal decisions by passing an input from one layer to the next.Neural networks, as the name suggests, tries to follow the pattern ...
Read MoreHow does the Q-table help determine the next action for the 'agent' in terms of reinforcement learning in Machine Learning?
We previously understood how Q-learning works, with the help of Q-value and Q-table. Q-learning is a type of reinforcement learning algorithm that contains an ‘agent’ that takes actions required to reach the optimal solution. This is achieved with the help of Q-table that is present as a neural network. It helps take the right step that maximizes the reward, thereby reaching the optimal solution.Now, let us see how the agent uses the policy to decide on the next step that it needs to take to achieve optimum results.The policy considers the Q-values of all possible actions that could be taken, ...
Read MoreHow to display open cursors in Oracle?
Problem:You want to display open cursors in Oracle.SolutionWe can query the data dictionary to determine the number of cursors that are open per session. "V$SESSION" provides a more accurate number of the cursors currently open than "V$OPEN_CURSOR".Exampleselect a.value , c.username , c.machine , c.sid , c.serial# from v$sesstat a , v$statname b , v$session c where a.statistic# = b.statistic# and c.sid = a.sid and b.name = 'opened cursors current' and a.value != 0 and c.username IS NOT NULL order by 1, 2;The OPEN_CURSORS initialization parameter determines the maximum number of cursors a session can have open.
Read MoreHow to identify SQL queries with the most waits in Oracle?
Problem:You want to identify the SQL statements responsible for the most waits in your database.SolutionWe can use below SQL statement to identify SQL causing problem.The below query will rank SQL statements that ran during the past 30 minutes and display them as per the total time waited by each query.ExampleSELECT ash.user_id, u.username, s.sql_text, SUM(ash.wait_time + ash.time_waited) ttl_wait_time FROM v$active_session_history ash, v$sqlarea s, dba_users u WHERE ash.sample_time BETWEEN sysdate - 60/2880 AND sysdate AND ash.sql_id = s.sql_id AND ash.user_id = u.user_id GROUP BY ash.user_id, s.sql_text, u.username ORDER BY ttl_wait_time ;When you have a performance ...
Read MoreHow to access values from previous or following rows in Oracle ?
You want to use Oracle aggregate function XMLAGG for string aggregation.?Solution:You would like to include calculations based on preceding and following rows in the result set.Oracle supports the LAG and LEAD analytical functions to provide access to multiple rows in a table, utilizing preceding or following logic and you won’t need to resort to joining the source data to itself. To demonstrate the usage we will use the students data.The LAG function can be used to see which student/s joining followed another, and also to calculate the elapsed time between joining.SQL: Identify the student joining informationExampleSELECT first_name, ...
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