Everything about Machine Learning

Everything about Machine Learning

Everything about Machine Learning

In this article we'll discuss Everything about Machine Learning.

What is Machine Learning?

Machines can learn by analyzing large amount of data. For example, rather than being programmed to recognize a cat or Human face, they can be trained with images from which to generalize and recognize specific objects.

How does machine learning relate to Artificial Intelligence?

Machine learning is a category of research and algorithms focused on finding patterns in data and using those patterns to make predictions. Machine learning falls within the Artificial Intelligence(AI) umbrella, which in turn intersects with the broader field of knowledge discovery and Data Mining.

How Machine Learning Works?

  1. Select Data: Split the data you have into three groups; training data, validation data, and test data.
  2. Model Data: Use the training data to build the model using the relevant features.
  3. Validate Model: Access the model with your validation data.
  4. Test Model: Check performance of the validated model with your test data.
  5. Use the model: Deploy the fully trained model to make predictions on new data.
  6. Tune Model: Improve performance of the algorithm with more data, different features, or adjusted parameters.

How Machine Learning fits in?

  1. Traditional Programming: A Software Engineer writes a problem that solves the problem.
  2. Statistics: An analyst compares the relationship of variables.
  3. Machine Learning: A data scientist uses a training data set to teach the computer what to do, and the system carries out the tasks.
  4. Intelligent Apps: The intelligent apps leverage the outputs of AI, as in this precision farming examples that uses drone based data collection.

Machine Learning in Practice

Here are just a few of many ways we've put machine learning to work.

  1. Rapid 3D mapping and Modeling- For a railway bridge reconstruction, PwC Data Scientists and Domain experts applied machine learning to data captured from drone. The combination enabled precise monitoring and quick feedback on work in progress.
  2. Enhanced profiling to mitigate risks- To detect insider trading PwC combined machine learning with other Analytic techniques to develop more comprehensive user profiles and gain deeper insite into complex suspicious behavior.
  3. Predicting the top performers- PwC used Machine Learning and other analysis to evaluate the potential of different horses running in the race.

Also Read- Best tools to make apps


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