As AI and ML are applied across multiple channels and industries, large corporations invest in these fields, increasing the demand for ML and AI experts. Based on trend search results on indeed.com, Jean Francois Puget of IBM’s machine learning department stated that Python is the most popular language for AI and ML. Python has many features that are useful for AI and machine learning, making it the best language for these purposes. It’s no surprise that Python is used in various industries for prediction and other machine learning tasks. Students can opt for Python AI ML Course in Chennai to build their careers in their respective fields.
Furthermore, let’s explore some of the common uses cases of python for prediction in various industries:
- Travel
- Healthcare
- Transportation
- Fintech
Now, let’s discuss in detail each use case.
- Travel
Skyscanner, for example, used a Python unsupervised ML algorithm to predict the behaviour of new aeroplane routes. They compared thousands of origins and destinations, evaluating each using 30 different criteria to determine passenger demand. Their findings are displayed on a dashboard, where you can select any origin city to view the groups of destinations numbered from 0 to 9 and their characteristics. This type of AI implementation in the travel industry is beneficial for recommending destinations to users, assisting in the creation of marketing budgets, and establishing an initial price for new routes. You can find many Python AI ML Courses In Delhi that will help you explore the importance and uses of Python in AI & ML.
- Healthcare
AI is reshaping the healthcare industry by assisting in the prediction and scanning of diseases, the detection of injuries, and the maintenance of good health on a daily basis through simple mobile applications. There are numerous excellent AI-based projects in the industry. Fathom, for example, is a natural language processing system designed to analyse electronic health records with the mission of “automating medical coding.” Their leaders have come from companies such as Google, Amazon, and Facebook and universities such as Stanford and Harvard. Another startup, AiCure, is focused on ensuring that patients take the right medications at the right time. They use face recognition, pill recognition, and action recognition to accomplish this.
- Transportation
Using Python, Uber created the ML platform Michelangelo PyML. They use it to solve day-to-day tasks using online and offline predictions. Michelangelo PyML is an extension of the original Michelangelo product, which was scalable but inflexible. Models can now be validated with PyML and then replicated in Michelangelo for maximum efficiency and scalability.
- Fintech
AI in financial services helps to solve problems related to risk management, fraud prevention, personalised banking, automation, and other tools that aid in providing high-quality financial services to users. AI in fintech is expected to reduce operating costs by 22% by 2030, resulting in a staggering $1 trillion in savings. Venmo, Affirm, and Robinhood are successful examples of Python-based online banking software. These services not only allow users to make and control payments and purchases, but they also create a social network within the software, allowing people to stay connected. When it comes to cryptocurrency, Python is used to create solutions like Anaconda that effectively analyse the market, make predictions, and visualise data.
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