Question

Different applications of machine learning

Answer 1

As we move forward into the digital age, One of the modern innovations we’ve seen is the creation of Machine Learning. This incredible form of artificial intelligence is already being used in various industries and professions. For Example, Image and Speech Recognition, Medical Diagnosis, Prediction, Classification, Learning Associations, Statistical Arbitrage, Extraction, Regression. Today we’re looking at all these Machine Learning Applications in today’s modern world.

If you are not familiar with Machine Learning, So you can read our Previous blog onMachine Learning Introduction.

2. Machine Learning Applications

Let us discuss all the real world Machine Learning Applications one by one-

2.1. Image Recognition

One of the most common uses of machine learning is image recognition. There are many situations where you can classify the object as a digital image. For digital images, the measurements describe the outputs of each pixel in the image.

In the case of a black and white image, the intensity of each pixel serves as one measurement. So if a black and white image has N*N pixels, the total number of pixels and hence measurement is N2.

In the colored image, each pixel considered as providing 3 measurements to the intensities of 3 main color components ie RGB. So N*N colored image there are 3 N2 measurements.

For face detection – The categories might be face versus no face present. There might be a separate category for each person in a database of several individuals.For character recognition – We can segment a piece of writing into smaller images, each containing a single character.  The categories might consist of the 26 letters of the English alphabet, the 10 digits, and some special characters.2.2. Speech Recognition

Speech recognition (SR) is the translation of spoken words into text. It is also known as “automatic speech recognition” (ASR), “computer speech recognition”, or “speech to text” (STT).

In speech recognition, a software application recognizes spoken words. The measurements in this application might be a set of numbers that represent the speech signal. We can segment the signal into portions that contain distinct words or phonemes. In each segment, we can represent the speech signal by the intensities or energy in different time-frequency bands.

Although the details of signal representation are outside the scope of this program, we can represent the signal by a set of real values.

Speech recognition applications include voice user interfaces. Voice user interfaces are such as voice dialing, call routing, domotic appliance control. It can also use as simple data entry, preparation of structured documents, speech-to-text processing, and plane.

2.3. Medical Diagnosis

ML provides methods, techniques, and tools that can help solving diagnostic and prognostic problems in a variety of medical domains. It is being used for the analysis of the importance of clinical parameters and of their combinations for prognosis, e.g. prediction of disease progression, for the extraction of medical knowledge for outcomes research, for therapy planning and support, and for overall patient management. ML is also being used for data analysis, such as detection of regularities in the data by appropriately dealing with imperfect data, interpretation of continuous data used in the Intensive Care Unit, and for intelligent alarming resulting in effective and efficient monitoring.

It is argued that the successful implementation of ML methods can help the integration of computer-based systems in the healthcare environment providing opportunities to facilitate and enhance the work of medical experts and ultimately to improve the efficiency and quality of medical care.

In medical diagnosis, the main interest is in establishing the existence of a disease followed by its accurate identification. There is a separate category for each disease under consideration and one category for cases where no disease is present. Here, machine learning improves the accuracy of medical diagnosis by analyzing data of patients.

The measurements in this application are typically the results of certain medical tests (example blood pressure, temperature and various blood tests) or medical diagnostics (such as medical images), presence/absence/intensity of various symptoms and basic physical information about the patient(age, sex, weight etc). On the basis of the results of these measurements, the doctors narrow down on the disease inflicting the patient.

2.4. Statistical Arbitrage

In finance, statistical arbitrage refers to automated trading strategies that are typical of a short term and involve a large number of securities. In such strategies, the user tries to implement a trading algorithm for a set of securities on the basis of quantities such as historical correlations and general economic variables. These measurements can be cast as a classification or estimation problem. The basic assumption is that prices will move towards a historical average.

Answer 2

Artificial intelligence and Machine learning

Artificial intelligence is the intelligence of humans used by computers with the help of simulation. The all machines and computers which we use today works with the help of Humans. Means, they don't have their own capacity to think and take decisions. The computers which we use today works with the help of Operating system (OS). Which make the connection between the humans and computers. The Artificial intelligence is the future of this planet.

Artificial intelligence is categorized in 2 different groups : Weak and strong. Because of which, Artificial intelligence is easy to understand and design. It's obvious that the Artificial intelligence is the future of this world and in the future of this world, we will see the all computers and phones who can think themselves.

Lot of companies today are working on Artificial intelligence and its need to this world. Because, the all tech and software development companies know the importance of Artificial intelligence in the future. Therefore, so many companies are today working on this Artificial intelligence field. Because of which, there is a lot of chance to get a Job in the field on Artificial intelligence.

Google, Microsoft, Facebook, Twitter and many internet based popular sites are today working on the development of the Artificial intelligence. This all companies are trying to make the Artificial intelligence more better to get the world with the advanced technologies.

Artificial intelligence is created by the deep learning algorithms because of which, Artificial intelligence can work better and more efficient. Artificial intelligence and Machine learning

Artificial intelligence can costs very expensive because of the Hardware and the software components. Artificial intelligence is used in this world today also for many purposes and it will be used in future also. The word which we hear as Robot is based on the Artificial intelligence. Artificial intelligence means the Computers can think themselves with their own efficiency.

Artificial intelligence is having the following efficiencies:

• Image and text recoganization: With the help of Artificial intelligence, it will be very easy to recognize any kind of image and the languages found in history. Artificial intelligence can recognize an image and it can give it's information and all required data to the scientists for the research work.
• Face recoganization: This is as similar to above one. In this technology, scientists are working for the Artificial intelligence face recognize. With the help of this, it will be very helpful to find the face of criminals.
• Software and program development: As humans can today develop the apps and programs, Artificial intelligence will be able to create and develop the software and programs. Because of which, the huge work of humans will be saved.

APPLICATIONS:

• Image recognization
• Chatbots
• Natural language
• Speech recognization

Software and Hardware for training:

• GPU
• Like spark
• Cloud data storage

Types of models:

• Deep learning
• Machine learning
• Neural learning

Programming languages used:

• Java
• Python
• C
• Tensorflow

Machine learning: Machine learning is very different from the AI concept. Machine learning is the way of teaching to the computers by programming them. Suppose, if we teach any computer or machine to do any specified work, then the machine can do that specified work for long time with no error.

Because of which, Machine learning is also used in some websites. Because of which, they can track our data and can show the ads related to the products and articles which we read and see on the internet.

Advantages and dis-advantages of Artificial intelligence:

Advantages:

1. AI can be used in business for growing our business or getting any ideas related to it. Artificial intelligence can also do the repeated work for long time, because of which Employees can decreased and business can increase.  
2. AI is also used in the treatments of the body. In short, Artificial intelligence is also used in the smart healthcare for finding the problems in the body. Because of which, treatment is error free.
3. Artificial intelligence is also used in education. The students can attract to the way of teaching of Artificial intelligence robots. Because of which, High grading students can be there. They can also teach the students in the digital way.
4. AI is also used in Manufacturing of machines. Artificial intelligence can do the work for long time with no mistake and error.

Disadvantages:

1. If the robots will think the opposite about humans, then the end of this earth will be not so far.
2. Robots can do the any illegal work which is not allowed in country.. Because of which, there can be a jail to its developer.
3. Artificial intelligence robots can steal the information and they can send it to the other governments. Because of which, there is a chance to be 3rd world war.
4. AI can kill the humans, if humans will scold or train it other way.