At the threshold of a new decade, artificial intelligence and its subset, machine learning promise a future led by rapid algorithmic advancements. However, machine learning development for enterprises requires a comprehensive understanding of the underlying machine learning algorithms and techniques.
Oodles AI shares this elaborative guide for choosing the right ML algorithm to build enterprise-grade applications.
Comprehending Machine Learning and its Types
“AI and its offshoot, machine learning, will be a foundational tool for creating social good as well as business success.” – Mark Hurd, Oracle CEO
Machine learning, at its core, is the practice of making intelligent computer systems that can learn automatically from experiences. These experiences or to say, data constitutes the foundational grounds of machine learning algorithms or sets of rules. With the world generating over 2.5 quintillions of data each day, machine learning algorithms are growing stronger for-
a) Solving complex problems
b) Making predictions
c) Improving performance
d) Formulating strategies, and a lot more.
Contrary to traditional computer programs, machine learning algorithms are able to learn autonomously from rich data without being explicitly programmed. It is on the basis of data availability that we categorize machine learning into four broad types-
1) Supervised Learning
Data is labeled, i.e. clearly annotated with output for the ML model to train its algorithms. Under supervised learning, ML models are fed with examples tagged with exact answers that the algorithm should fetch on its own.
For instance, a labeled dataset of fruits would first train the model with distinct images of apples, bananas, et al. Once trained, the model should be able to predict correct fruit names in a different image
2) Semi-supervised Learning
Data is both labeled and unlabeled. While labeled data provides annotations for essential data, ML algorithms learn from the labeled inputs to label the unlabeled data. The methodology is gaining significant success in extracting relevant features from complex and labor-intensive datasets.
Deploying Machine Learning Algorithms With Oodles
AI and machine learning are propelling business intelligence to build innovative solutions for several enterprise challenges.
We, at Oodles, are skilled professionals with working knowledge of different machine learning and its algorithms. Our AI team has hands-on experience in deploying top-notch machine learning algorithms for serving dynamic business use cases, such as-
a) Facial recognition for employee attendance
b) Diabetes prediction model
c) COVID-19 risk assessment chatbots
d) Image caption generator, and more.
In addition to machine learning, we provide custom chatbot development services using NLP algorithms.
Learn more: All About Machine Learning Algorithms