As we move into the future, our trading processes will become more and more efficient due to artificial intelligence and algorithmic trading. Algorithms are already a part of our lives. Think of social media, the internet, advertising, industry, financial markets, and every other application where computer systems and processes are required to carry out day-to-day data collection and execution.
You may ask, what is an algorithm? It is a set of instructions that a computer follows to complete a job. It can be compared to someone baking a cake. The only difference is that the recipe is the set of instructions, and the baker is a computer.
The finance world is making use of algorithms for trading and investing in the stock markets. How does this affect your role as a trader in the future? Quite possibly, computers will be trading for you!
Will the stock market shift to machine learning?
I certainly believe so, as machine learning is more efficient. Artificial Intelligence will reduce the risk in high volatility markets, remove the emotional side of trading, and collect data and learn at a faster pace than human beings.
The advantage that machine learning has over algorithmic trading is that artificial intelligence can learn on its own. In contrast, algorithmic systems are a man-made set of rules that computers are programmed to follow. The trader can watch and see the machine learn and advise, allowing the trader to understand why the AI builds up the strategy for entering or exiting a trade versus the black box experience of algorithms.
For autonomous driving to be successful, two key components are required. One being Maps for direction (e.g., Google Maps or Waze), and the second being driving skill for decision making (Waymo or Tesla FSD). Similarly, for autonomous trading to be successful in its decision-making, it requires the following components: fundamental analysis for price direction and technical analysis for price action.
Leading experts in the field of machine learning
There are many companies that are leading the field of machine learning, but here are some of the most prominent ones:
- Amazon Web Services (AWS): AWS is a subsidiary of Amazon and provides on-demand cloud computing platforms and APIs. It offers a range of machine learning services, such as AWS SageMaker, which is a fully managed service that allows data scientists to build, train, and deploy machine learning models quickly1.
- Databricks: Databricks was founded in 2013 by the original creators of Apache Spark, a popular open-source framework for big data processing and analytics. Databricks provides a unified platform for data and AI on lakehouse architecture, which combines the best of data lakes and data warehouses. Databricks enables data scientists to handle data preparation, exploration, model training, and large-scale predictions2.
- Dataiku: Dataiku is a software company that offers an end-to-end platform for data science and machine learning. Dataiku enables users to collaborate on data projects, from data ingestion and preparation, to feature engineering and model building, to deployment and monitoring. Dataiku supports a variety of machine learning techniques, such as supervised, unsupervised, and deep learning3.
- Veritone: Veritone is a company that specializes in artificial intelligence for media and entertainment. Veritone provides a cloud-based platform that allows users to access and analyze various types of media content, such as audio, video, and text, using cognitive engines powered by machine learning. Veritone also offers solutions for content monetization, compliance, and security4.
- DataRobot: DataRobot is a company that automates the process of building and deploying machine learning models. DataRobot leverages the best practices and expertise of top data scientists to create a platform that can handle any type of data, any size of data, and any machine learning problem. DataRobot also provides features for model validation, interpretation, and governance5.
These are just some of the examples of the leading machine learning companies in the world. There are many more companies that are using machine learning to innovate and solve various challenges across different domains and industries. Machine learning is a rapidly evolving and expanding field that offers many opportunities for growth and learning.
* This is a contributed article and this content does not necessarily represent the views of techtimes.com