The concept in defense of cyber attacks on Archangel is the e learning machine. What is e learning machine? Let’s look at the reviews below
History of Machine Learning
Since the first time a computer was created, humans have thought about how to get computers to learn from experience. This was proven in 1952, Arthur Samuel created a program, game of checkers, on an IBM computer. The program can learn movements to win the game of checkers and save the movement into its memory.
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The term machine learning is basically a computer process for learning from data. Without data, the computer will not be able to learn anything. Therefore if we want to learn machine learning, we will definitely continue to interact with data.
All machine learning knowledge will definitely involve data. Data can be the same, but the algorithm and the approach are different to get optimal results.
Machine Learning is one branch of the Artificial Intelligence discipline that discusses the development of systems based on data. Many things are learned, but basically there are 4 main things learned in machine learning.
Focused Learning (Supervised Learning)
Non-directed Learning (Unsupervised Learning)
To find out more about Machine Learning, you can directly learn from professor Andrew Ng in Stanford University.
Machine Learning Application
Examples of the application of machine learning in life are as follows.
For example, application in the field of medicine is detecting a person’s disease from symptoms that exist. Another example is detecting heart disease from recording an electrocardiogram.
In the field of computer vision, the application of face recognition and face labeling as on Facebook. Another example is handwriting translation into text.
In the case of information retrival, language translation using computers, converting sounds into text, and spam email filters.
One technique for applying machine learning is supervised learning. As we discussed earlier, machine learning without data is not going to work. Therefore the first thing need to be prepared is data. Data will usually is divided into 2 groups, namely training data and testing data.
Training data will be used to train algorithms to find suitable models, while testing data will be used to test and find out the model performance obtained at the testing stage.
From the model obtained, we can make predictions that are divided into two types, depending on the type of output. If the results of the prediction are discrete, they are called the classification process.
Impact of Machine Learning in the Community
The application of machine learning technology has now inevitably been felt. At least there are two conflicting effects from the development of machine learning technology. They are: positive and negative impacts.
One of the positive impacts of machine learning is the opportunity for entrepreneurs and technology practitioners to continue working in developing machine learning technology. The help of human activities must be one of the positive effects of machine learning.
For example, there is a spelling checking feature for each language in Microsoft Word. Manually checking will take days and involve a lot of energy to get perfect writing. But with the help of the spelling checking feature, we can see real-time errors that occur during typing.
But besides that, there are a negative impacts that we must be aware of. The existence of labor cuts because their works have been replaced by machine learning technology. This is the problem that must face. Especially, the dependence on technology that now increasingly felt
Humans will be more lulled by the ability of their gadgets so they forget to learn to do activities without the help of technology.