Artificial Intelligent-IV

Artificial Intelligent-IV

Hello ,

             So  we have go forward to learn new about Artificial Intelligent Series. In this post I have introduce you with Machine Learning, Artificial Intelligent And  Deep Learning Topics. First I have introduce about these three topic and then the difference of that.
                

                                          
Artificial intelligence(AI)

            AI is the most comprehensive way to think about the best of advanced computer intelligence. At the Dartmouth Artificial Intelligence Conference held in 1956, AI was suitably described as: “Every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.” It can range from a computer program playing chess or a voice-recognition system like Alexa by Amazon that is capable of speech response and interpretation.

Machine Learning (ML)

            ML is a subfield of AI. The core principle of ML is that machines learn by themselves by taking data from various sources. Presently, it is considered to be one of the most promising tools of the AI kit that is suitable for businesses.

            ML systems are capable of fast application of knowledge and getting trained from large sets of data to be able to do tasks like speech recognition, facial recognition, translation, and object recognition with ease and efficiency. ML allows machines to make predictions based on the recognition of complex data sets and patterns. This is what makes ML different from hand-coding a software program that requires specific instructions for task completion.

Deep Learning

            Deep learning is one of the subsets of machine learning. Whenever the term deep learning is used,  it is generally referred to the deep artificial neural networks, and at times of deep reinforcement learning. Deep artificial neural networks are algorithm sets are extremely accurate especially for problems like sound recognition, image recognition, recommender systems, etc. A few examples would be – deep learning is a part of DeepMind’s popular AlphaGo algorithm, which had beaten former world champion Lee Sedol at Go in 2016, and the current world champion Ke Jie in 2017.

            Deep is a technical term referring to the layers of the neural network. A superficial network has a single hidden layer, and a network that is deep has multiple layers. These hidden layers are the layers that allow deep neural networks to acquire data features from a feature hierarchy. This is due to the fact that simple features recombine from the existing layers to form complex features. Intensive computations form the basis of deep learning, and this is why GPUs are in great demand- to provide training in the deep-learning models.

Difference

              After the above information you have getting enough idea About AI,ML and Deep Learning. So the is some difference on these three fields can described below.

  

            While discussing about Artificial intelligence vs Machine learning vs Deep learning, one needs to understand that data lies at the heart of everything. Whether it is an algorithm that is being used or machine learning or artificial intelligence, one aspect is certain: if flawed data is being used, the extracted information and insights would most definitely be flawed. Algorithms can be flawed quite like the humans that they are replacing but more the usage of data more is the scope for flaws.

             Therefore data cleansing becomes critical. Data cleansing is defined as the process of correcting and detecting inaccurate or corrupt records from a table, record set, or database and deleting/ modifying irrelevant/incorrect data. According to the Crowd Flower Data Science report, data scientists need to cleanse data though it is not something that they enjoy doing. A major part of their time is spent in data cleansing since the output needs to be trustworthy and this can only happen when data is cleansed.

            The concept of Artificial intelligence is broader than that of machine learning, the latter uses computers to imitate the cognitive human functions. Artificial intelligence, therefore, can be defined as machines carrying out various tasks based on algorithms in a perfectly intelligent way. Machine learning is a subset of AI and its’ focus lies on the capability of machines to not only receive data sets but also learn and relearn for themselves, change the algorithms according to the information that they are processing.

            Deep learning networks need to visualize large quantities of items to be trained. Instead of being programmed with the edges that define items, the systems learn from exposure to millions of data points. An early example would be of Google Brain learning to recognize cats after being shown over ten million images. Deep learning networks do not need to be programmed with the criteria that define items; they are able to identify edges through being exposed to large amounts of data.

            So we have understanding the concept of Artificial intelligence, Machine learning, Deep learning. And there difference also. This information can take some time to read,but it’s very interesting because it can provide some important knowledge about Artificial Intelligent. I hope it will help you to grow your knowledge on AI.

Keep in touch to next article on series of AI. Thank you.