Plotting

Results


Challenges of Artificial Intelligence -- From Machine Learning and Computer Vision to Emotional Intelligence

arXiv.org Artificial Intelligence

Artificial intelligence (AI) has become a part of everyday conversation and our lives. It is considered as the new electricity that is revolutionizing the world. AI is heavily invested in both industry and academy. However, there is also a lot of hype in the current AI debate. AI based on so-called deep learning has achieved impressive results in many problems, but its limits are already visible. AI has been under research since the 1940s, and the industry has seen many ups and downs due to over-expectations and related disappointments that have followed. The purpose of this book is to give a realistic picture of AI, its history, its potential and limitations. We believe that AI is a helper, not a ruler of humans. We begin by describing what AI is and how it has evolved over the decades. After fundamentals, we explain the importance of massive data for the current mainstream of artificial intelligence. The most common representations for AI, methods, and machine learning are covered. In addition, the main application areas are introduced. Computer vision has been central to the development of AI. The book provides a general introduction to computer vision, and includes an exposure to the results and applications of our own research. Emotions are central to human intelligence, but little use has been made in AI. We present the basics of emotional intelligence and our own research on the topic. We discuss super-intelligence that transcends human understanding, explaining why such achievement seems impossible on the basis of present knowledge,and how AI could be improved. Finally, a summary is made of the current state of AI and what to do in the future. In the appendix, we look at the development of AI education, especially from the perspective of contents at our own university.


Machine Learning Towards Intelligent Systems: Applications, Challenges, and Opportunities

arXiv.org Artificial Intelligence

The emergence and continued reliance on the Internet and related technologies has resulted in the generation of large amounts of data that can be made available for analyses. However, humans do not possess the cognitive capabilities to understand such large amounts of data. Machine learning (ML) provides a mechanism for humans to process large amounts of data, gain insights about the behavior of the data, and make more informed decision based on the resulting analysis. ML has applications in various fields. This review focuses on some of the fields and applications such as education, healthcare, network security, banking and finance, and social media. Within these fields, there are multiple unique challenges that exist. However, ML can provide solutions to these challenges, as well as create further research opportunities. Accordingly, this work surveys some of the challenges facing the aforementioned fields and presents some of the previous literature works that tackled them. Moreover, it suggests several research opportunities that benefit from the use of ML to address these challenges.


Deep Learning Prerequisites: Logistic Regression in Python

#artificialintelligence

Online Courses Udemy | Deep Learning Prerequisites: Logistic Regression in Python Data science techniques for professionals and students - learn the theory behind logistic regression and code in Python BESTSELLER Created by Lazy Programmer Inc.  English [Auto-generated], Portuguese [Auto-generated], 1 more Students also bought Natural Language Processing with Deep Learning in Python Data Science: Natural Language Processing (NLP) in Python Deep Learning: Advanced Computer Vision (GANs, SSD, +More!) Unsupervised Machine Learning Hidden Markov Models in Python Modern Deep Learning in Python Preview this course GET COUPON CODE 100% Off Udemy Coupon . Free Udemy Courses . Online Classes


Complete Machine Learning and Data Science: Zero to Mastery

#artificialintelligence

Created by Andrei Neagoie, Daniel Bourke Students also bought Machine Learning A-Z: Hands-On Python & R In Data Science Data Science A-Z: Real-Life Data Science Exercises Included Machine Learning, Data Science and Deep Learning with Python Statistics for Data Science and Business Analysis Data Science 2020: Complete Data Science & Machine Learning Preview this Udemy Course GET COUPON CODE Description This is a brand new Machine Learning and Data Science course just launched January 2020 and updated this month with the latest trends and skills! Become a complete Data Scientist and Machine Learning engineer! Join a live online community of 270,000 engineers and a course taught by industry experts that have actually worked for large companies in places like Silicon Valley and Toronto. Graduates of Andrei's courses are now working at Google, Tesla, Amazon, Apple, IBM, JP Morgan, Facebook, other top tech companies. Learn Data Science and Machine Learning from scratch, get hired, and have fun along the way with the most modern, up-to-date Data Science course on Udemy (we use the latest version of Python, Tensorflow 2.0 and other libraries).


Udemy Machine Learning: Decent course, excellent community

#artificialintelligence

This post is part of "AI education", a series of posts that review and explore educational content on data science and machine learning. When it comes to software development education, I'm a classical type: I prefer books over video tutorials, and I like to manually write every single line of code instead of copy-pasting from sample files and Stack Exchange. My early experience with online artificial intelligence and machine learning courses had mostly left me disappointed. So, when Udemy gave me access to their online course "Machine Learning A-Z: Hands-On Python & R In Data Science," I was a bit skeptical. But after going through the course, I must say that the instructors, Kirill Eremenko and Hadelin de Ponteves, have done a great job to make machine learning, a fairly complicated topic, accessible to a wide audience.


Machine learning python

#artificialintelligence

With modern technology, such questions are no longer bound to creative conjecture. You have just found Keras. Today i will give a brief introduction over this topic which created headache for me when i was learning this. All video and text tutorials are free. I use Anaconda package that almost wraps up all the Python packages including Jupyter notebook.


45 Best Data Science Certification for Data Scientists JA Directives

#artificialintelligence

Are you looking for Best Data Science Degree Online? This Online Data Science Course list will help you to become a top Data Scientist. Data science or data-driven science is one of today's fastest-growing fields. Do you want to become a Data Scientist in 2019? The list of the Data Science Degree will give you a clear idea from data science definition to expert's levels. If you don't know how to get data scientist certification then this data science certificate programs online will help you to get an online data science certificate. You will be able to get Microsoft data science certification or even Harvard data science certificate with this excellent collection of online courses. Also, this Data Science training will give you an idea about data science, python, data scientist, big data, analytics, machine learning, deep learning and Artificial Intelligence (AI) which are the most booming topics now. You can be a data science master in a short period of time. All big companies, publishers, advertisers, and other industries are now highly depended on data science or machine learning. So, it is high time to learn some skills in data science, for example, get the high demanded Data Science online certifications. How does it work at the present time, why data scientist's career and data science jobs are in top position? If you like a trendy career, you have that opportunity right now and get hired by the big industries. At the same time, online entrepreneurs and business personals also need to update themselves with the fundamental machine learning skills to compete with the fast-moving industry. Below are few best Data Science online courses that might assist you to jump-start the knowledge of data science sector. Best Data Science online tutorial and programs listing displays the'Best Course,' 'Product Description,' 'Rating,' 'Students Enrolled' 'Product's Image' and as well as an Enroll button to purchase the Courses from respective learning platforms for your convenience. Description: If you want to become a successful data scientist then you should take this course. Just learning statistics, data visualization and data wrangling is not enough. You also need to know how to ask the right questions and tell the right story from your data. Description: If you want to learn machine learning then this is the perfect course for you. Two professional data scientists designed this course so that you can learn the theory and algorithms behind the machine learning. If you just learn the coding libraries then you will not know what is actually going on in the back end. In fact, you will not be able to perform well in the industries. Which is why this is a very good course to get started into the machine learning world. The course also includes study materials about coding libraries.


What Should I Learn First: Introducing LectureBank for NLP Education and Prerequisite Chain Learning

arXiv.org Machine Learning

Recent years have witnessed the rising popularity of Natural Language Processing (NLP) and related fields such as Artificial Intelligence (AI) and Machine Learning (ML). Many online courses and resources are available even for those without a strong background in the field. Often the student is curious about a specific topic but does not quite know where to begin studying. To answer the question of "what should one learn first," we apply an embedding-based method to learn prerequisite relations for course concepts in the domain of NLP. We introduce LectureBank, a dataset containing 1,352 English lecture files collected from university courses which are each classified according to an existing taxonomy as well as 208 manually-labeled prerequisite relation topics, which is publicly available. The dataset will be useful for educational purposes such as lecture preparation and organization as well as applications such as reading list generation. Additionally, we experiment with neural graph-based networks and non-neural classifiers to learn these prerequisite relations from our dataset.


Top 10 Machine Learning, Deep Learning, and Data Science Courses for Beginners (Python and R) - DZone AI

#artificialintelligence

The first programming exercise "Twitter Sentiment Analysis in Python" is both fun and challenging, where you analyze tons of twitter message to find out the sentiments e.g.


Why Do Developers Find It Hard To Learn Machine Learning?

#artificialintelligence

Machine learning (ML) is touted as the most critical skill of current times. Artificial intelligence (AI), an application of ML, is becoming pervasive. From autonomous vehicles to self-tuned databases, AI and ML are found everywhere. Industry analysts often refer to AI-driven automation as the job killer. Almost every domain and industry vertical are getting impacted by AI and ML.