The Future of Machine Learning
From your favorite streaming platform’s recommendation algorithm to self-driving cars, Machine Learning has grown its presence in our daily lives exponentially. In fact, the global Machine Learning market is projected to grow to $117.19 billion by 2027. Thus, it is without a doubt that businesses and industries should begin utilizing these technologies to their advantage.
What is Machine Learning?
Machine Learning is a type of artificial intelligence that offers systems the ability to learn without being programmed explicitly. In Machine Learning, algorithms are used to receive and analyze input data to predict output values. Essentially, it is a technology that uses information and data gathered from the past to create new predicted outcomes in the future.
3 Types of Machine Learning Algorithms
Supervised Learning - The machine is taught by example
The operator provides the Machine Learning algorithm with a known dataset that includes desired inputs and outputs, and the algorithm must find a method to determine how to arrive at those inputs and outputs.
Unsupervised Learning - The machine studies data to identify patterns
There is no answer key or human operator to provide instruction. Instead, the machine determines the correlations and relationships by analyzing available data on its own.
Reinforcement Learning - The machine is given a set of actions, parameters, and end values
By defining the rules, the Machine Learning algorithm then tries to explore different options and possibilities, monitoring and evaluating each result to determine which one is optimal.
Industries Utilizing Machine Learning to Watch Out For
Healthcare and Pharmaceutical - Each year, the healthcare industry generates immense amounts of data. By utilizing Machine Learning disciplines, better predictions and treatments can be made:
Disease Prediction → Traditionally, disease prediction only includes limited variables like age, weight, height, and gender. However, with a Machine Learning approach, a wider range of variables can be analyzed to create more accurate results for disease prediction.
Drug Discovery → In the healthcare industry, drug development is extremely expensive and time-consuming. In fact, the median cost of bringing a new drug to market is $985 million. However, by analyzing past datasets with a drug compound’s chemical structure, Machine Learning algorithms may make this process much more efficient by predicting the effect of drug compounds on different cells and genes or even possible side effects.
Manufacturing - Currently, only a small percentage of the manufacturing industry utilizes Machine Learning. However, businesses that leverage Machine Learning have great advantages in their business processes:
Facilitating Processes → Traditionally, human supervisors are tasked with monitoring equipment performance and condition. However, Machine Learning technologies may be used to complete this task along with predicting product quality or energy consumption.
Automation → With the rise of robots that use Machine Learning to perform certain complex tasks, businesses may work more efficiently and create products in cost-effective ways by automating many of their processes.
Automotive - Popular car development companies like Tesla, Waymo, or General Motors have been investing in the development and deployment of self-driving cars. However, none have created fully autonomous vehicles yet. With Machine Learning, this technology may become a reality.
Deep Learning → Deep learning, a type of Machine Learning algorithm, may be utilized to improve the perception and navigation of self-driving vehicles. This includes technologies such as path planning or obstacle avoidance. By analyzing vast amounts of past driving data, autonomous vehicles are able to learn and function more safely on the road.
Conclusion
Machine Learning is, without a doubt, a technology that is highly lucrative with endless potential. Investing early and being mindful of these capabilities for Machine Learning and Artificial Intelligence will certainly be advantageous across multiple industries and businesses.
