Hoy traemos a este espacio el último número de iJET International Journal of Emerging Technologies in Learning (iJET) This interdisciplinary journal aims to focus on the exchange of relevant trends and research results as well as the presentation of practical experiences gained while developing and testing elements of technology enhanced learning. So it aims to bridge the gap between pure academic research journals and more practical publications. So it covers the full range from research, application development to experience reports and product descriptions. Readers don't have to pay any fee. Vol 14, No 06 (2019) Table of Contents Papers Setting Up and Implementation of the Parallel Computing Cluster in Higher Education Meruert Serik, Nursaule Karelkhan, Jaroslav Kultan, Zhandos Zulpykhar Design and Implementation of Web-Based English Autonomous Learning System A Semantic Distances-Based Approach for a Deeply Indexing of Learning Objects Kamal El Guemmat, Sara Ouahabi Design of Students' Spoken English Pronunciation Training System Based on Computer VB Platform Application of 3D Visualization in Landscape Design Teaching Wenbo Jiang, Yuan Zhang Application of Artificial Intelligence in Autonomous English Learning among College Students Application of Computer Data Analysis Technology in the Development of a Physical Education Examination Platform Fan Cheng, Yiwei Yin Data Mining-based Design and Implementation of College Physical Education Performance Management and Analysis System Yimeng Fan, Yu Liu, Haosong Chen, Jianlong Ma A Novel Machine Translation Method based on Stochastic Finite Automata Model for Spoken English Accelerating Qurán Reading Fluency through Learning Using QURÁNI Application for Students with Hearing Impairments Yusuf Hanafi, Heppy Jundan Hendrawan, Ilham Nur Hakim Short Papers The Effect of Presenting Anomalous Data on Improving Student's Critical Thinking Ability Saiful Prayogi, Muhali Muhali, Sri Yuliyanti, Muhammad Asy'ari, Irham Azmi, Ni Nyoman Sri Putu Verawati Highly Efficient English MOOC Teaching Model Based on Frontline Education Analysis The Development of Digital Book of European History to Shape the Students' Democratic Values Ulfatun Nafiáh, Mashuri Mashuri, Daya Negri Wijaya International Journal of Emerging Technologies in Learning (iJET) – eISSN: 1863-0383 (leer más...) Fuente: [iJET ]

Hoy traemos a este espacio el último número Vol 14, No 19 (2019) del International Journal of Emerging Technologies in Learning (iJET) This interdisciplinary journal aims to focus on the exchange of relevant trends and research results as well as the presentation of practical experiences gained while developing and testing elements of technology enhanced learning. So it aims to bridge the gap between pure academic research journals and more practical publications. So it covers the full range from research, application development to experience reports and product descriptions.

From drones for food delivery and robots for automation to COVID-19 contact tracing apps, and online education learning platforms, we've seen a great acceleration in adoption of different technologies in the past few months. Technology has been a great pillar of strength during the pandemic and it's also going to help redefine the post COVID-19 world. Now, different businesses and industries will benefit from different technologies, but there are some common ones that are likely to dominate the world after COVID-19. Nuff said, let's take a look at some of the tech trends that are likely to see a surge in adoption post COVID-19. We know this one's too obvious but that's for a reason - AI is playing a massive role in helping us all get through the pandemic and it will see a greater adoption after the pandemic is over.

Hoy traemos a este espacio esta conferencia titulada: "AI in Education: Transforming Education using Personalised Adaptive Learning" by Amar Lalwani #ODSC impartida en Agosto de 2019 en Begaluru, India There has been a significant rise in the gross enrolment ratio of the students in public schools over the past few decades. However, there is a decline in their learning outcomes, which results from staff crunch, crowded classrooms and insufficient infrastructure. Moreover, students are learning less as they move to higher classes. National Achievement Survey - 2017 shows that the national average score of a grade 8 student was barely 40% in Maths, Science and Social Studies. The survey also highlights the fact the country is short of at least 10 lakhs qualified teachers.

Daphne Koller is best known as the cofounder of Coursera, the open database for online learning that launched in 2012. But before her work on Coursera, she was doing something much different. In 2000, Koller started working on applying machine learning to biomedical data sets to understand gene activity across cancer types. She put that work on hold to nurture Coursera, which took many more years than she initially thought it would. She didn't return to biology until 2016 when she joined Alphabet's life science research and development arm Calico.

A recent line of work has shown a qualitative equivalence between differentially private PAC learning and online learning: A concept class is privately learnable if and only if it is online learnable with a finite mistake bound. However, both directions of this equivalence incur significant losses in both sample and computational efficiency. Studying a special case of this connection, Gonen, Hazan, and Moran (NeurIPS 2019) showed that uniform or highly sample-efficient pure-private learners can be time-efficiently compiled into online learners. We show that, assuming the existence of one-way functions, such an efficient conversion is impossible even for general pure-private learners with polynomial sample complexity. This resolves a question of Neel, Roth, and Wu (FOCS 2019).

Proficiency in mathematics is essential for aspirants to get started with their data science journey. A strong foundation in mathematics will help beginners to not only learn existing and new machine learning techniques easily but also differentiate themselves from others in the competitive market. Consequently, data science aspirants must ensure that they master algebra, calculus, probability, among others before diving deep into machine learning. Here are top courses on mathematics that aspiring data scientists must take into account while devising their learning strategy. The five-week-long course on Coursera can be the starting point for learners as linear algebra has a wide range of applications in data science practices.

Ensemble Machine Learning in Python: Random Forest, AdaBoost 4.6 (1,193 ratings) Course Ratings are calculated from individual students' ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately. In recent years, we've seen a resurgence in AI, or artificial intelligence, and machine learning. Machine learning has led to some amazing results, like being able to analyze medical images and predict diseases on-par with human experts. Google's AlphaGo program was able to beat a world champion in the strategy game go using deep reinforcement learning. Machine learning is even being used to program self driving cars, which is going to change the automotive industry forever.

You keep hearing about machine learning and artificial intelligence and how they revolutionize the world we live in. You want to learn more. You have basic understanding of Python and you are decent in math. You're going to learn hands-on machine learning with scikit-learn, a Python library for machine learning. Since this is a hands-on course, you will be working your way through with Python and Jupyter notebooks.

We can't hang out somewhere nice, it's been so long since we last met our friends or families who are stuck overseas and we can't hope for a major change or revolution because the future is that uncertain and this uncertainty just grows every day. It's miserable and sad to see the current state people are in, but kudos to the people who are fighting with their or their loved ones' lives every day, struggling in these trying times, and to the front liners in the health sector who are trying their best to put every possible effort to provide and save the lives of the masses.