Machine learning Tools

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Machine Learning Tools
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What is Machine Learning??

• Machine learning is an application of
  artificial intelligence (AI) that provides
  systems the ability to automatically learn and
  improve from experience without being explicitly
  programmed. Machine learning focuses on the
  development of computer programs that can access
  data and use it learn for themselves. It is seen
  as a subset of artificial intelligence. Machine
  learning algorithms build a mathematical
  model based on sample data, known as "training
  data", in order to make predictions or decisions
  without being explicitly programmed to do
  so. Machine learning algorithms are used in a
  wide variety of applications, such as email
  filtering and computer vision, where it is
  difficult or infeasible to develop conventional
  algorithms to perform the needed tasks.

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Importance of Machine Learning

• Data is very important for all the businesses.
  Data-driven decisions increasingly make the
  difference between keeping up with competition or
  falling further behind. Machine learning can be
  the key to unlock the value of corporate and
  customer data and enacting decisions that keep a
  company ahead of the competition. The machine
  learning field is continuously evolving. And
  along with evolution comes a rise in demand and
  importance.

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Popular Machine Learning Tools

• 1. Scikit-learn
•  Scikit-learn is for machine learning development
  in python. It provides a library for the Python
  programming language. It helps in data mining and
  data analysis. It provides models and algorithms
  for Classification, Regression, Clustering,
  Dimensional reduction, Model selection, and
  Pre-processing.
• Advantages- Easily understandable documentation
  is provided. Parameters for any specific
  algorithm can be changed while calling objects.

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• 2. PyTorch
•  PyTorch is a Torch based, Python machine
  learning library. The torch is a Lua based
  computing framework, scripting language, and
  machine learning library. It helps in building
  neural networks through Autograd Module. It
  provides a variety of optimization algorithms for
  building neural networks. PyTorch can be used on
  cloud platforms. It provides distributed
  training, various tools, and libraries.
• Advantages- It helps in creating computational
  graphs. Ease of use because of the hybrid
  front-end.

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• 3. TensorFlow
• TensorFlow provides a JavaScript library which
  helps in machine learning. APIs will help you to
  build and train the models. It helps in training
  and building your models. You can run your
  existing models with the help of TensorFlow.js
  which is a model converter. It helps in the
  neural network.
• Advantages- You can use it in two ways, i.e. by
  script tags or by installing through NPM. It can
  even help for human pose estimation.

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• 4. Weka
• These machine learning algorithms help in data
  mining. The features are Data preparation,
  Classification, Regression, Clustering,
  Visualization and Association rules mining.
• Advantages are it provides online courses for
  training and it is easy to understand algorithms.

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• 5. Knime
• Knime is a tool for data analytics, reporting and
  integration platform. Using the data pipelining
  concept, it combines different components for
  machine learning and data mining. It can
  integrate the code of programming languages like
  C, C, R, Python, Java, JavaScript etc. It can
  be used for business intelligence, financial data
  analysis, and CRM.
• Advantages are it can work as a SAS alternative.
  It is easy to deploy and install and easy to
  learn.
• Disadvantages are it is difficult to build
  complicated models and has limited visualization
  and exporting capabilities.

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• 7. Apache Mahout
• Apache Mahout helps mathematicians,
  statisticians, and data scientists for executing
  their algorithms. It provides algorithms for
  Pre-processors, Regression, Clustering,
  Recommenders, and Distributed Linear Algebra.
  Java libraries are included for common math
  operations. It follows Distributed linear algebra
  framework.

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About Henry Harvin

• Henry Harvin is a leading career and competency
  development organization with focus on value
  creation. We are into the business of training,
  skill development, assessment centres, content
  services and higher education. Our dream is to
  establish 'Henry Harvin' in line with the vision
  of Mr.Henry Dunster 400 years ago which now
  resonates in the form of a prestigious
  educational institution respected worldwide.

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• If you are interested to know more about Machine
  Learning, join the Certified Machine Learning
  Practitioner Course by Henry Harvin.