Do you want to understand machine learning? How it works and how is correlated to artificial intelligence and deep learning? If yes, then keep reading....
Machine Learning is based on mathematics, specifically statistics. It is a probabilistic discipline that began in the 1950s. Despite initial enthusiasm, research and development in Machine Learning languished for over 30 years, suffering from twin ills of a lack of data to work with and computers that were too slow to effectively work with what data they had.
It is no accident Machine Learning is coming into its own over the last 10 years. Until we began creating and storing massive amounts of data about our world, Machine Learning was mostly an idea in the minds of statisticians. And until computers reached a level of speed and power where these massive data sets could be ingested in a reasonable amount of time, the revolution couldn’t happen.
Most machine learning technology is developed in such a way that it is excellent at performing one or, at most, two tasks. By focusing entire technology on one single task, they can ensure that it runs that task perfectly and that it does not get confused between the tasks that it is trying to accomplish.
It is likely that as we become more familiar with machine learning technology and more educated in the algorithms, we will start to see more and more machines completing multiple tasks, rather than just one.
This audiobook gives a comprehensive guide on the following:
- What is machine learning?
- Machine learning categories
- Sectors and industries that use machine learning
- Fundamental algorithms
- Regression analysis
- Benefits of machine learning
- Deep learning
- Deep neural network
- Big data analytics
- Big data analysis tools
- How companies use big data
- Data mining and applications
- And more!
What are you waiting for? Listen now!