If a machine behaves like humans is referred as Artificial intelligence. We at CSI offers the Artificial intelligence thesis writing services for M tech and PhD research scholars. Ability of the artificial intelligence is rationalise and take action to achieve a specific goal. Learning and making the perception by the machine is AI and used in various industries such as finance, healthcare, and e-commerce.
Artificial intelligence can be divided into two categories such as strong and weak. Not only the machine learning and deep learning is artificial intelligence but it is broader are which includes Machine Learning, Deep Learning, reinforcement learning, Computer Vision, Robotics, Natural Language Process, Recommender systems, IoT, Neuromorphic Computing, Expert Systems, Fuzzy Logics and Neural Networks. Some of the application of the artificial intelligence are medical diagnosis, engineering, remote sensing, construction and manufacturing and other industries. Artificial intelligence real life examples are chat boats (Siri, Alexa), Netflix, Face recognition and online customer support.
Current topics in the field of Artificial Intelligence for research, thesis, and project:
Deep Learning
• Natural Language Processing
• Artificial Neural Network
• Expert Systems
• Computer Vision
• Fuzzy Systems
• Machine Learning
• Biometrics
• Robotics
• Computational Biology

Following are the list of of topics on which we can provide you the dissertation. Kindly choose your preference and inform us accordingly.

Machine Learning

In the machine learning, a machine is made intelligent not by the specific programming but by task from the previous experience.  In this machine learns automatically without human intervention. The process of learning starts with the developing the model using training of the quality data sets and algorithms. The choice of algorithms depends on what type of data do we have and what kind of task we are trying to automate.

However, generally speaking, Machine Learning Algorithms are divided into 3 types i.e. Supervised Machine Learning Algorithms, Unsupervised Machine Learning Algorithms, and Reinforcement Machine Learning Algorithms.

Reinforcement learning is a machine learning process to human beings. The reinforcement algorithm is based on learn and reward. Machine learns from own mistakes. This means that the algorithm decides its next action by learning behaviours that are based on its current state and that will maximize the reward in the future. And like humans, this works for machines as well! For example, Google’s AlphaGo computer program was able to beat the world champion in the game of Go (that’s a human!) in 2017 using Reinforcement Learning.

Deep Learning

Deep learning is the specific field of Machine Learning. It is uses the working of human brain for data processing and decision making. Deep learning uses the Artificial Neural Networks to implement the machine leaning. These neural networks are connected in a web-like structure like the networks in the human brain. Which finds its application in speech recognition, computer vision, natural language processing, drug discovery,and bioinformatics. An example of a deep neural network is RankBrain which is one of the factors in the Google Search algorithm.

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