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Dataset

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Model Selection

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Save Result

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machine learning

Learn The Fundamentals

Identifying the most appropriate machine learning techniques and using them optimally can be challenging for the best of us. MLA Solver is a place where you can share interesting datasets with the people who love to analyse data, and build the best solutions together, saving you valuable time, increasing your visibility, and speeding up discovery.

MLA Solver links data to algorithms and people, so you can build on the state of the art and learn to teach machines to learn better

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It starts with data

Upload your datasets, or link them from existing repositories. MLA Solver automatically versions and analyses each dataset. Solves the data sets using several machine learning algorithms and display the result as output.

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machine learning

Frequently Asked Questions

Machine Learning solves Real-World problems. Unlike the hard coding rule to solve the problem, machine learning algorithms learn from the data. The learnings can later be used to predict the feature. It is paying off for early adopters. A full 82% of enterprises adopting machine learning and Artificial Intelligence (AI) have gained a significant financial advantage from their investments. According to Deloitte, companies have an impressive median ROI of 17%.

Supervised learning is a machine learning algorithm of inferring a function from labeled training data. The training data consists of a set of training examples.
Example
Knowing the height and weight identifying the gender of the person. Below are the popular supervised learning algorithms.
  • Support Vector Machines
  • Regression
  • Naive Bayes
  • Decision Trees
  • K-nearest Neighbour Algorithm and Neural Networks.

Unsupervised learning is also a type of machine learning algorithm used to find patterns on the set of data given. In this, we don’t have any dependent variable or label to predict.

Unsupervised Learning Algorithms:
  • Clustering
  • Anomaly Detection
  • Neural Networks and Latent Variable Models

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