The future of machine learning – Everything you should Know about machine learning technology
The wave of Machine Learning has hit and transformed every sector, affecting the way we take our decisions. The widespread use of Big Data among all the industries has sparked the use of machines to detect patterns and previse future. With multiple complicated territories which Machine Learning has been able to conquer such as data mining, natural language processing (NLP), image recognition, and expert systems, it is said to be the foundation of future civilization.
Machine Learning is a very promising approach of Artificial Intelligence, one which is radically reshaping the present and the future! Learn more about the difference between Machine learning and Artificial intelligence.
MACHINE LEARNING AND ITS WORKING
Machine learning is actually a bottomless pit. It encompasses a lot of things.
The assumption laying the ground for Machine Learning is the analytical solutions that are reached by studying previous data models. It is the process whereby Artificial Intelligence is developed in computers to make them work without being programmed and as efficiently as a human mind but with little or no effort. It makes use of statistical analysis and predictive analysis to carry out the assigned task.
HOW IT WORKS
Three types of techniques are employed by Machine Learning, which trains and predicts the output.
1. SUPERVISED MACHINE LEARNING- Input (X) and output (Y) variables are fed to the supervised algorithm which then puts them to use by mapping inputs to the desired outputs. It is called supervised machine learning since it requires human interference for making predictions in the testing data. A number of iterations help in getting the acceptable level of output. Common applications of this procedure are:
• Linear or Logistic regression
• Naive Bayes
• Support Vector Machines
• Discriminant Analysis
• Random Forest
• K-Nearest Neighbors
2. UNSUPERVISED MACHINE LEARNING- There is no outcome variable in unsupervised machine learning. The algorithm works out the data using input variable and comes up with a similar structure. It forms classifications and associations in data. The fields where it comes in use are:
• Gaussian Mixture
• Neural Networks
• K-means and Hierarchial clustering
• Apriori algorithm for association rule mining
3. REINFORCEMENT LEARNING- Here the machine generates programs, called agents using the process of learning and evolving. The conclusion is drawn from previous results and repercussions and the best method is selected through trial and error.
APPLICATIONS OF MACHINE LEARNING
With all the intensifying hype around Machine Learning, the world top technology companies are under pressure to exploit it further, and soon, to come up with more if its features and ways in which it can be utilized.
Nevertheless, you will be shocked to discover the diversification of machine learning as well as how much you are already making use of it unknowingly!
Machine learning has proved worthy in many industries globally. Some of the staunch users of ML are:
Machine Learning is a pro at detecting any anomaly. It can flag any malpractice and malfunction in high volume and high-frequency data transfer and communication. Inside trading in stock markets and fraudulent transactions are quickly and efficaciously caught.
Whether it be a language barrier or a matter of text-to-speech and vice verse, all make use of ML.
Visual recognition, Tone Analyzer, chat box, retrieving and ranking the relevant information, and personality insights have been using Machine Learning.
Healthcare organizations make use of Machine Learning. It picks out similar patterns between the patients and diseases. The biometric sensors have been saving lives globally. To determine the effectiveness of treatment in clinical treatments machine learning is employed.
Fraud detection and face recognition first began in the financial sector to catch theft. Since then through further improvisation and method, it has been meticulously working through structured and unstructured data.
In businesses better forecasting plays an intricate and crucial role. The constant and irregular fluctuation makes it difficult to comprehend the demand variability. But now, Machine Learning in business provides a business solution for demand forecasting.
The recommendation and suggestions, market analysis, customer sentiments analyzation, ad ratings, and identification of new markets, Machine Learning has helped the retailers increase their sales and grow their business.
FORECASTS FOR MACHINE LEARNING
In the near future, the technology world is about to witness tremendous growth in Smart Apps, Virtual reality, Virtual Assistants, and substantial use of Artificial Intelligence. The mobile market will escalate by the use of machine learning, and we will soon enter the era of self-driven cars (they have already been launched for testing and trials). Machine Learning is already an incredibly powerful tool which has been solving complicated problems. Although new Machine Learning tools would pop up now and then, the skills required to tune them and jazz them up would forever be in demand.
MACHINE LEARNING A CONTROVERSY?
The disadvantages that would come along with the evolution of Machine Learning are:
• An overwhelmingly automated lifestyle would make the human race vulnerable to threats and misfortunes!
• Things would be robbed of genuineness, and the look and feel of originality would be replaced by fakeness.
• The human resolve and inter-dependency would be eliminated which is the core of human civilization. Are we prepared to lose ourselves completely? Is it worth being a technology servant?
Author Bio: –
Article name – the future of machine learning
The article “the future of machine learning” is guest posted on the Tech Knol by Victoria Ashley, a professional content writer always seeking opportunities to write on. Ashley associated with a Trucks & Equipment business as a trainer and content analyst!