Collaborating Authors

Neural Networks



CNN(Convolution neural network)在深度學習領域中已經發展得相當成熟,從2012年Alexnet發表以來,到現在2022年依然在許多領域維持著相當好的成績,其中在電腦視覺領域中效果尤其顯著。許多視覺模型使用卷積層(Convolution…

Choose Laptop For Machine Learning And Computervision (2022)


Choosing a laptop is currently the best choice for computer vision and deep learning. In fact, due to the shortage of microchips in manufacturing and mining, the prices of video cards are very high and the laptop is a good alternative. We will see how to choose a laptop, usable in computer vision with good results, based on the main characteristics. To choose the right laptop the main component to consider is the graphics card. In this, the reference brand is Nvidia because most of the libraries are compatible with this graphics card.

Pan-African Artificial Intelligence and Smart Systems


This book constitutes the refereed post-conference proceedings of the First International Conference on Pan-African Intelligence and Smart Systems, PAAISS 2021, which was held in Windhoek, Namibia, in September 2021. The 17 revised full papers presented were carefully selected from 41 submissions. The theme of PAAISS 2021 was "Advancing AI research in Africa" and the papers are arranged according to subject areas: Deep Learning; Classification and Pattern Recognition; Neural Networks and Support Vector Machines; Smart Systems.

The hype around DeepMind's new AI model misses what's actually cool about it


One of DeepMind's top researchers and a coauthor of the Gato paper, Nando de Freitas, couldn't contain his excitement. "The game is over!" he tweeted, suggesting that there is now a clear path from Gato to artificial general intelligence, or AGI, a vague concept of human- or superhuman-level AI. The way to build AGI, he claimed, is mostly a question of scale: making models such as Gato bigger and better. Unsurprisingly, de Freitas's announcement triggered breathless press coverage that DeepMind is "on the verge" of human-level artificial intelligence. This is not the first time hype has outstripped reality.

Various Challenges for Applying Machine Learning in Healthcare


Machine Learning is being used in many industries such as automobile, manufacturing, and retail industries. With the development of machine learning and deep learning algorithms, there are a huge number of useful predictions such as predicting the stock prices, house prices and loan default prediction. Furthermore, there is data available in different formats that could be used for machine learning predictions. As the data keeps growing, there is a lot of scope for development in the field of machine learning, and predictions are going to get better and better in the future. One of the interesting applications of machine learning is in the field of healthcare.

Perception for Self-Driving Cars -- Free Deep Learning Course


An important use for computer vision and deep learning is self driving cars. Perception and Computer Vision forms about 80% of the work that Self Driving Cars do to drive around. If you want to improve your deep learning skills, this is a great topic to learn about. We just published a deep learning course on the Sakshay is a machine learning engineer and an excellent teacher.

How to get start with Machine Learning and Data Science


This is the course where Dr.Andrew Ng beautifully teaches fundamental algorithms in Machine learning and underlying Math. Deep Learning is the thing using very extensively in almost every domain in current tech world. And the same to learn Deep Learning and want to become future Research Scientist/Machine Learning scientist/Data Scientist anything the best way to get start is to take Deep Learning Specialisation and this one also taught by favourite professor Dr.Andrew Ng through coursera. In this specialisation you will be taught everything every fundamental thing to get start with Deep Learning. There are also very predominant courses to get a complete package, everything there in AI with industry ready skills such as-- Applied AI Course by Chekuri Srikanth Varma through Applied Roots and Scalar Academy.

The Download: DeepMind's AI shortcomings, and China's social media translation problem

MIT Technology Review

Earlier this month, DeepMind presented a new "generalist" AI model called Gato. The model can play the video game Atari, caption images, chat, and stack blocks with a real robot arm, the Alphabet-owned AI lab announced. All in all, Gato can do hundreds of different tasks. But while Gato is undeniably fascinating, in the week since its release some researchers have got a bit carried away. One of DeepMind's top researchers and a coauthor of the Gato paper, Nando de Freitas, couldn't contain his excitement.

100+ Best Blogs To Learn Machine Learning In 2022


Hi Everyone, Hope you all are fine and safe. Today, In this post, We'll share a handpicked list of 100 active, regularly updated and some of the best Artificial Intelligence, Machine Learning and Deep Learning blogs & communities. Let's dive in this huge collection of some of the popular machine learning blogs and top deep learning blogs every beginner, intermediate and advanced ML enthusiast should follow or check. Sebastian is a research scientist in the language team at DeepMind. At, the author shares articles about natural language processing, machine learning, and deep learning. A glimpse to some of his articles include "Recent Advances in Language Model Fine-tuning", "An Overview of Multi-Task Learning in Deep Neural Networks" and more. A Must follow blog for machine learning and deep learning enthusiast. You should follow this blog because the articles are written by a senior director of Artificial Intelligence at Tesla. Andrej Karpathy is also a founding member of one of the best non profit AI company named OpenAI.

The Story of Autoencoders - Machine Learning Mindset


Imagine you speak in front of a microphone, and your sound will be transformed into text! Imagine you talk to a chatbot, and the chatbot wants to answer your question. To create a powerful generative model, the machine must always understand data, whether in a supervised or unsupervised way. The generative model needs first to understand the data and then create a robust understanding called data representation in the AI world. There are tons of generative models out there.