Category: Machine Learning
Classification and Regression Demystified in Machine Learning
Classification predictive output is a label and for regression its a quantity. Generative algorithms can also be used as classifiers. It just so happens that they can do more than categorising the input data. Can call classification as sorting and regression as connecting technique as well.
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Machine Learning – Introduction to Unsupervised Learning
Unsupervised learning is classified as one of the three categories of machine learning, alongside Supervised Machine Learning, and Reinforcement Learning. Specifically, it falls under the domain of Unsupervised Machine Learning (UML). The predominant technique utilized in the Unified Modeling Language (UML) is cluster analysis. Cluster analysis is employed as a means of discovering concealed patterns or categories within data beyond conventional analytical methods.
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How Machine Learning Algorithms Works : An Overview
Machine learning involves the use of computational methods that enable algorithms to derive significant insights from data without being limited by pre-existing equations. The ML algorithms analyze data using statistical methods to uncover meaningful patterns and relationships. These insights can then be used to make predictions or decisions automatically, without requiring any specific programming instructions.
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Machine Learning – Introduction to Supervised Learning
AILabPage defines Machine Learning as “A focal point where business, data and experience meets emerging technology and decides to work together”. SML through historic data set is able to hunt for correct answers, and the task of the algorithm is to find them in the new data. Supervised Machine Learning is
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Machine Learning – Introduction to Quick and Accurate Machine Translation
Machine translation model renders text from one natural language to another. There are various MT models developed to effectively drive translation based application souls. To accomplish this task, experts rely on the powerful approaches used to build these models..
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Why GDPR will Make Machine Learning not so legal
Does GDPR require Machine Learning algorithms to explain their output? may be yes may be no or in short Probably not, but there is enough ambiguity to be clarified and keep DataScientists, Lawyers, industry influencers busy.
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Astonishing Hierarchy of Machine Learning Needs
Present-day technology has allowed machines to achieve skills previously exclusive to humans, such as improved decision-making abilities and game proficiency. The ability for machines to analyze and recognize patterns and subsequently retain this information for future reference has made it achievable. Nowadays, the biggest challenge lies in locating capable resources who can display and distinguish their knowledge acquired from practical business scenarios rather than indulging in online debates with others, as found in university and PhD literature.
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Reinforcement Learning – Reward for Learning
Reinforcement learning can be understood by using the concepts of agents, environments, states, actions and rewards. This is an area of machine learning; where there’s no answer key, but RL agent still has to decide how to act to perform its task. The agent is inspired by behaviourist psychology who decide how and what actions will taken in an environment to maximize some notion of cumulative reward.
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Unsupervised Learning an Angle for Unlabelled Data World
System does self-discovery of patterns, regularities and features etc. from the input data and relations for the input data over output data. Discovering similarities and dissimilarities to forms clusters i.e. self-discovery is main target here. Since the examples given to the learner are unlabeled
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Supervised Machine Learning – Insider Scoop for labelled data
Machine learning algorithms “learns” from the observations. When exposed to more observations, the algorithm improves its predictive performance. What’s going to happen to the stock market tomorrow? Is a task of deducing function from labeled training data.
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The Exciting Evolution of Machine Learning
Machine learning is the process of a machine attempting to accomplish a task, independent of human intervention, more efficiently and more effectively with every passing attempt i.e learning phase. At this point, AI- a machine which mimics the human mind, is still a pipe dream. In the middle we have the meat of the pipeline, the model, which is the machine learning algorithm that learns to predict given input data.
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How to Friends with Statistics and MachineLearning
While there may be variances in methodology between machine learning and statistics, these distinctions do not sever the alliance between the two fields. The contrast lies in the fact that machine learning prioritizes enhancing efficiency and achieving optimal results, while the others focus on sample size, population, and developing hypotheses. The primary focus of machine learning is on producing accurate forecasts, even if the explanations behind those predictions are not easily comprehensible.
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FinTech – Machine Learning and Recommenders
These terms are used to from BI Intelligence, To illustrate the various applications of AI in eCommerce and use case studies to show how this technology has benefited merchants/ecommerce service providers. Different consumers have varying, and often very specific, requirements for product, needs, expect performance, cost of consumption, silicon wafer thin kind of cost for best thing in mind and other parameters.
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AI The Epicenter of eCommerce
In our todays online shopping how much is artificial intelligence. How artificial intelligence can help retailers to deliver the highly personalized experiences shoppers desire. Ant colony optimization algorithm (To formulate training feed-forward neural networks with ant colony optimization) to obtain the users’ preference information are widely used in todays ecommerce business for comparison-shopping to solve the problem of the user bias’ filtering and learning. The performance improvements are important to both consumers / buyer and sellers / merchants.
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Robots and Artificial Intelligence
As per professor Andrew machine learning is a revolution in history of man kind first one was where machines came and took our basic jobs to make us faster and our life easy. Now to me this second one is coming to make us lazy and heavily dependent. The technique that made easy work easy possibly is no longer AI, but something mundane.
