Applications of Machine learning
3 min readNov 13, 2023
- Image Recognition- Most common application of machine learning. It is used to identify objects, persons, places, digital images etc. The popular use is image recognition and face detection is, Automatic friend tagging used by facebook. Here the technology behind this is machine learnings algorithms.
- Speech recognition- the ability of a machine or program to identify words spoken aloud and convert them into readable text. Speech recognition, also known as automatic speech recognition (ASR), computer speech recognition, or speech-to-text, is a capability which enables a program to process human speech into a written format. E.g. Google assistant, Siri, Cortana, and Alexa are used speech recognition technology.
- Trafic alerts- Traffic Prediction is a task that involves forecasting traffic conditions, such as the volume of vehicles and travel time, in a specific area or along a particular road. This task is important for optimizing transportation systems and reducing traffic congestion.- Real time location of the vehicle from Google Map app and sensors. Average time has taken on past days at the same time.
- Product Recommendation- Product recommendation is a popular application of machine learning that aims to personalize the customer shopping experience. By analysing customer behaviour, preferences, and purchase history, a recommendation engine can suggest products more likely to interest a particular customer. As similar, when we use Netflix, Hotstar, we find some recommendations for entertainment serials, movies.
- Self-Driving cars- is a vehicle that uses a combination of sensors, cameras, radar and artificial intelligence (AI) to travel between destinations without a human operator.
- E-mail spam and malware filtering-By analyzing various email attributes such as sender information, subject line, content, and embedded URLs, machine learning algorithms can identify spam characteristics and make accurate predictions. The emails we receive are automatically filtered automatically to important, normal and spam.
- Virtual personal assistant- At present, machine learning algorithms are widely used by various applications of speech recognition. Google assistant, Siri, Cortana, and Alexa are using speech recognition technology to follow the voice instructions. AI catboats employ natural language processing (NLP) and machine learning (ML) algorithms to understand user input, produce pertinent responses and improve their performance over time by learning from these interactions.
- Online Fraud detection- fraud detection systems are using machine learning algorithms to analyse vast amounts of data in real time, identifying patterns and anomalies to flag potential fraudulent activities. These systems can be trained on historical data, improving their accuracy and effectiveness over time.
- Stock Market Trading- Machine learning (ML) is playing an increasingly significant role in stock trading. Predicting market fluctuations, studying consumer behavior, and analyzing stock price dynamics are examples of how investment companies can use machine learning for stock trading. ML technology is often used in the finance industry to predict stock prices and influence trading decisions. It works by using large historical data sets to make predictions about the future.
- Medical diagnosis- Machine learning can detect patterns of specific diseases. It can then alert clinicians to any irregularities. In this way, artificial intelligence becomes the second set of eyes. AI can also assess a patient’s health based on knowledge collected from large data sets. Diagnostic tests not only help doctors understand all the aforementioned aspects, but they will also allow doctors to assess whether the chosen treatment is effective in curing or stopping the progression of a certain condition. The system processes the symptoms provided by the user as input and gives the output as the probability of the disease. Naïve Bayes classifier is used in the prediction of the disease which is a supervised machine learning algorithm. The probability of the disease is calculated by the Naïve Bayes algorithm.
- Automatic language translation-Machine translation is the process of using artificial intelligence to automatically translate text from one language to another without human involvement.
