The content of this course changes as technology evolves, to keep up to date with changes follow me on GitHub. Deep learning is a group of exciting new technologies for neural networks. Through a combination of advanced training techniques and neural network architectural components, it is now possible to create neural networks that can handle tabular data, images, text, and audio as both input and output. Deep learning allows a neural network to learn hierarchies of information in a way that is like the function of the human brain. This course will introduce the student to classic neural network structures, Convolution Neural Networks (CNN), Long Short-Term Memory (LSTM), Gated Recurrent Neural Networks (GRU), General Adversarial Networks (GAN) and reinforcement learning.

Do you want to begin a career in Artificial Intelligence? If yes, then this webinar is for you! The AI-900 certification takes you through Azure AI Fundamentals and therefore is a great first step in your AI journey. In this Free Webinar, we will introduce you to the basic concepts of Azure AI and help you understand the benefits of taking up this certification, exam preparation methods, recommended resources, and much more. We will also have our own AI experts facilitate this session to give you the best insights possible! Who Can Attend? Absolutely Anybody! What’s In It For You? 1. Learn from Microsoft Certified in-house experts who curate our training modules for industry professionals to address their unique requirements. 2. Get access to CloudThat’s Exam Ready Assessment Platform, where you can practice exam questions and assess your preparedness before taking the AZ-500 certification exam.

Data science is an essential part of many industries today. It is the field of applying advanced analytics techniques and scientific principles to extract valuable information from data for business decision-making, strategic planning, and other uses. A data scientist's job is to analyze data for actionable insights. Specific tasks include: Identifying the data analytics problems that offer the greatest opportunities to the organization. In this modern age of information technology, enormous chances are available to learn data science for self-study to become data scientists, can master the fundamentals of data science.

Hera re the some of the best deep learning courses you must learn in 2022 to boost your career in AI and Machine learning.

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A step-by-step tutorial to use Locust to load test a (pre-trained) image classifier model served using FastAPI. In my previous tutorial, we journeyed through building end-points to serve a machine learning (ML) model for an image classifier through an image classifier app, in 4 steps using Python and FastAPI. In this follow-up tutorial, we will focus on load/performance testing our end-points using Locust. If you have followed my last tutorial on serving a pre-trained image classifier model from TensorFlow Hub using FastAPI, then you can directly jump to Step 2 of this tutorial. In the app.py file, implement the /predict/tf/ end-point using FastAPI.

Continual Learning, also known as Lifelong Learning, aims to continually learn from new data as it becomes available. While prior research on continual learning in automatic speech recognition has focused on the adaptation of models across multiple different speech recognition tasks, in this paper we propose an experimental setting for \textit{online continual learning} for automatic speech recognition of a single task. Specifically focusing on the case where additional training data for the same task becomes available incrementally over time, we demonstrate the effectiveness of performing incremental model updates to end-to-end speech recognition models with an online Gradient Episodic Memory (GEM) method. Moreover, we show that with online continual learning and a selective sampling strategy, we can maintain an accuracy that is similar to retraining a model from scratch while requiring significantly lower computation costs. We have also verified our method with self-supervised learning (SSL) features.

In this blog, I am going to share my journey about Kaggle, That How I become Kaggle NotebooksExpert in 4 weeks. I will share tips and a proper road map to achieve this goal even I will tell you how many hours I spent on Kaggle. There are three other categories but I worked only on Notebooks till now. Kaggle Ranking is based on the Kaggle progression system. So basically if your notebook had 5 non-invoice votes you will earn a bronze medal.

Originally published on Towards AI the World's Leading AI and Technology News and Media Company. If you are building an AI-related product or service, we invite you to consider becoming an AI sponsor. At Towards AI, we help scale AI and technology startups. Let us help you unleash your technology to the masses. This article is the third part of the AI Ethics for Data Science essential series.