Learn about new concepts of AI, ML, DL

 

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Machine Learning:  ML is the field of study that gives computers the capability to learn without being explicitly programmed, it gives the computer that makes it more similar to humans: The ability to learn.

Deep Learning:  Deep learning is an artificial intelligence (AI) function that imitates the workings of the human brain in processing data and creating patterns for use in decision making. Deep learning is a subset of machine learning in artificial intelligence that has networks capable of learning unsupervised from data that is unstructured or unlabeled. Also known as deep neural learning or deep neural network. 

Types of Deep learning Networks:

Neural networks - Deep neural networks have more than one layer. For instance, Google LeNet model for image recognition counts 22 layers. 

• Feed forward Neural networks -  The simplest type of artificial neural network. With this type of architecture, information flows in only one direction, forward. 
• Recurrent Neural networks -  RNN is a multi-layered neural network that can store information in context nodes, allowing it to learn data sequences and output a number or another sequence. In simple words it an Artificial neural networks whose connections between neurons include loops.
• Convolutional Neural networks -  CNN is a multi-layered neural network with a unique architecture designed to extract increasingly complex features of the data at each layer to determine the output. CNN's are well suited for perceptual tasks. 
• Reinforcement learning -  Reinforcement learning is a subfield of machine learning in which systems are trained by receiving virtual "rewards" or "punishments," essentially learning by trial and error. 

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Artificial Intelligence: AI is concerned with building smart machines capable of performing tasks that typically require human intelligence. AI is an interdisciplinary science with multiple approaches, but advancements in machine learning and deep learning are creating a paradigm shift in virtually every sector of the tech industry.  

Natural Language Processing: Computers and Machines are great while working with tabular data or Spreadsheets. However, human beings generally communicate in words and sentences, not in the form of tables or spreadsheets, and most of the information that humans speak or write is present in an unstructured manner. So it is not very understandable for computers to interpret these languages. 

 

Therefore, In NLP, our aim is to make the computer’s unstructured text understandable and retrieve meaningful information from it.