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I am new to machine learning. I am familiar with SVM, Neural networks and GA. I'd like to know the best technique to learn for classifying pictures and audio. SVM does a decent job but takes a lot of time. Does anyone know a faster and better one? Also, I'd like to know the fastest library for SVM.

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Machine learning is a form of artificial intelligence (AI) that gives systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning concentrates on the development of computer programs that can access data and use it to learn for themselves.

Machine Learning Algorithms Every Engineer Should Know

  • Naïve Bayes Classifier Algorithm

  • K Means Clustering Algorithm

  • Support Vector Machine Algorithm

  • Apriori Algorithm

  • Linear Regression

  • Logistic Regression

  • Artificial Neural Networks

  • Random Forests

  • Decision Trees

  •  Nearest Neighbours 

One method called Ada-Boost, read this and this to know more about it, on the other hand, you can find lots of people are doing some research, for example in Gender Classification of Faces Using Adaboost.

If your main concern is speed, you should take a look at VW and generally at stochastic gradient descent based algorithms for training SVMs.

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