9 Deep Learning The Past Present and Future of Artificial
5) AI and Machine Learning Demystified
In this presentation, Carol Smith establishes that AI cannot replace humans.Smith conveys that AI can serve the purpose of enabling human beings in makingbetter decisions.The slides talk about how the actions of AI are the result of the human inputsgoing into its programming. An AI’s bias is not its own, but the human biaswith which it has been programmed, is emphasised on.Other issues such as the need for regulations and other considerations withinit that require deliberation are also touched upon. The presentation leavesyou with a message – Don’t fear AI, Explore it.* * *
9) Deep Learning – The Past, Present and Future of Artificial
IntelligenceThis presentation provides a comprehensive insight into deep learning.Beginning with a brief history of AI and introduction to basics of machinelearning such as its classification, the focus shifts towards deep learningentirely.Various kinds of networks such as recurrent neural nets and generativeadversarial networks have been discussed at length. Emphasis has been given toimportant aspects of these networks and other mechanisms such as naturallanguage processing (NLP).Detailed examples of practical applications and the scope of deep learning arefound throughout the presentation. However, this presentation may provedifficult for first time learner’s of AI to comprehend.* * *
Machine learning is the science of getting computers to act without beingexplicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastlyimproved understanding of the human genome.Machine learning is so pervasive today that you probably use it dozens oftimes a day without knowing it. Many researchers also think it is the best wayto make progress towards human-level AI.In this class, you will learn about the most effective machine learningtechniques, and gain practice implementing them and getting them to work foryourself.Furthermore, you’ll learn about not only the theoretical underpinnings oflearning, but also gain the practical know-how needed to quickly andpowerfully apply these techniques to new problems.Finally, you’ll learn about some of Silicon Valley’s best practices ininnovation as it pertains to machine learning and AI.
3. Artificial Intelligence Course
The Field of Artificial Intelligence (Ai systems) has more to give to theindustry. Experts are cultivating this field more than before. With greaterrecognition, this course has been evolved as the source of some highest payingjobs in the country currently.Artificial Intelligence has powered eminent sectors computer science, naturallanguage processing, mathematics, psychology, and neuroscience, machinelearning, and several other disciplines.A basic course in Ai will give an overview of the elements of Ai which wouldsmoothen your way to research and development till the time. You could alsogain hands-on expertise together with the Ai programming of intelligent agentssuch as search algorithms, logic, and gaming.These courses are practically implemented in self-driving cars, face andretina recognition, military drones, and language processors.
9. Machine Learning Course
A machine learning course is a popular one as it’s been there in the pictureacross the wide array of industries. It enables computers with thefunctionality of executing without any specific program or command.With the successful completion of this course, you can bag a job with alucrative package in India even if you are a fresher. Machine learning makes acomputer work effortlessly in alignment with the human behavioral pattern.
Artificial Intelligence and Machine Learning
Build your knowledge of the fundamental statistical models and numericaloptimizations of machine learning, including deep learning, with applicationsin computer vision, natural language processing and intelligent userinteraction.
Coursework focusing on tool-oriented and problem-directed approaches tomachine learning with applications in computer vision, natural languageprocessing, geopositioning, and voice & music.
Difference between AI and Machine Learning
These two terms are correlated to each other and use interchangeably. For thisreason, it creates lots of confusion in many of us brain.But, they are not the same term. Let’s understand with an example to clear ourwrong perception.If AI is – tree then ML is – one of the main Branch of treeAs we know, Artificial Intelligence is ‘Smart’ then who makes it smart? Offcourse the ‘Data’ and who feeds that data to AI? Yes, you are absolutely rightMachine Learning provide the data to AI.Machine Learning is a subset of Artificial Intelligence. We can say that thebackbone of AI is Machine Learning.Without Machine Learning machine can’t able to perform any task on its own.Therefore you have to get some knowledge of ML if you opt for ArtificialIntelligence as a career option.If you want to learn about Machine Learning and want to know various ML careerpaths check out this article; Machine Learning Career Path [Things You ShouldKnow]To become successful in the Artificial Intelligence career path you must havea clear understanding of how machine learns from scratch.Without ML AI is completely zero i.e. without ML there is a point of AI
Diploma in Artificial Intelligence
* A diploma in artificial intelligence after 12th is a very good option. * It is a short term training program. * PG Diploma in artificial intelligence is a postgraduate degree qualification i.e, it can be pursued only after a bachelors degree. * The course duration varies from a period of 1 year to 2 years.Candidates who do not have an AI or a computer science background can take updiploma courses to start a career in AI. The candidates who want to specializein AI usually go for a PG Diploma course.The average salary after a diploma in artificial intelligence ranges from INR2.5-8 lakh per annum.
Machine Learning Engineer
They design self-running softwares to automate predictive models. They developthe software in such a way that the machine learns from each operation and usethe results of each operation to carry out future operations with a greaterdegree of accuracy.Starting Salary: INR 6,91,892Skills Required * Python * Machine Learning * Deep Learning * Natural Language Processing * Computer Vision
Machine Learning Algorithm/Bayesian Algorithms
Machine learning is a study of computer algorithms. It is also called BayesianAlgorithm as it uses the Naive Bayes Theorem. It builds a mathematical modelbased on sample data, in order to make predictions or decisions without beingexplicitly programmed to do so.
Top Courses for Machine Learning Algorithms
Candidates can take up the following courses to have specialized knowledge inMachine learning algorithms.Rating | Course Name | Provider | Duration | Course Fees —|—|—|—|— 4.7 | Machine Learning Algorithm | Coursera | 9 hours | Free 4.6 | Bayesian Statistics | Udemy | 4.5 hours | INR 1,280 4.5 | Bayesian Methods of Machine Learning | Coursera | 32 hours | Free 4.5 | Machine Learning Algorithm | Udemy | 8.5 hours | INR 8,640 – | Naive Bayes from Scratch | Analytics Vidya | 6 months | Free
Machine Learning Algorithm Job Profiles
* Machine Learning Engineer * Data Scientist * Human-Centered Machine Learning Designer * Business Intelligence Developer