The African Development Bank held a workshop to convey the continent's immense investment and partnership opportunities to Asian business leaders, particularly as the continent seems poised to return to economic growth in 2021 following the impact of the COVID-19 pandemic. The two-hour virtual event, held in English, Korean, and Chinese, offered participants an opportunity to learn more about the Bank and its operations. The webinar comes on the heels of the recently launched African Economic Outlook 2020 -Asia Supplement, which revised growth projections and outlook for Africa for 2020 and 2021. "I take this opportunity to strongly encourage Asian private sector entities gathered here today, to partner with the Bank to take advantage of the multiple investment opportunities that exist on the continent," said Samuel Higenyi Mugoya, the Bank's Director for Syndication, Co-financing and Client Solutions Department, which co-organized the event, together with the Bank's Asia External Representation Office. In introducing the Bank, Takashi Hanajiri, Head of the Asia External Representation Office, provided an overview of the Bank and its history and components before providing a summary of its flagship Africa Investment Forum (AfricaInvestmentForum.com) initiative and the opportunities it offers.

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Through the Azure AI Camp, the ML practitioner will learn how to use Azure ML, Databricks, ML on the Edge and other Microsoft AI technologies to unlock insights on big datasets and deploy AI services to the cloud and edge. It is designed as a hands-on workshop experience, recommended in instructor-led format or on-demand learning by using the documentation and resources provided for guidance. In this workshop, the following resources will get provisioned. In practice, most are shared amongst an organization or group. For this workshop it will depend upon the Azure Subscription setup.

You must have heard/read people telling you that if you want to be a rockstar Data Science or Machine Learning Engineer then have a good grip on mathematical concepts like Linear Algebra, Calculus, Probability, etc. Mathematics is necessary to build products or conduct academic research in machine learning. Maths and Programming are highly intertwined in machine learning workflows. Often, the code is built directly from mathematical intuition and shares the syntax of mathematical notation. In this article, I'm going to cover the two best courses from the top university in the world, that you can take to build a solid foundation in calculus. Single Variable Calculus is a first-year, first-semester course at MIT.

NLP - Natural Language Processing with Python Learn to use Machine Learning, Spacy, NLTK, SciKit-Learn, Deep Learning, and more to conduct Natural Language Processing Bestseller What you'll learn Welcome to the best Natural Language Processing course on the internet! This course is designed to be your complete online resource for learning how to use Natural Language Processing with the Python programming language. In the course we will cover everything you need to learn in order to become a world class practitioner of NLP with Python. We'll start off with the basics, learning how to open and work with text and PDF files with Python, as well as learning how to use regular expressions to search for custom patterns inside of text files. Afterwards we will begin with the basics of Natural Language Processing, utilizing the Natural Language Toolkit library for Python, as well as the state of the art Spacy library for ultra fast tokenization, parsing, entity recognition, and lemmatization of text.

Time series analysis and forecasting is one of the key fields in statistical programming. Due to modern technology the amount of available data grows substantially from day to day. They also know that decisions based on data gained in the past, and modeled for the future, can make a huge difference. Proper understanding and training in time series analysis and forecasting will give you the power to understand and create those models. This can make you an invaluable asset for your company/institution and will boost your career!

Artificial Intelligence is a hot topic. Applications based on machine learning make the news on a near-daily basis. Smart police cameras steered by algorithms can register drivers holding cell phones with great precision. Algorithms can dynamically determine the real-time prices for taxi rides, hotel rooms, airplane seats, and so on. High-frequency traders are getting rich as they sleep by letting their secret algorithms do the work.

The way we work has changed and it's continuing to change. People are working remotely while being part of their team irrespective of the location. With this change, traditional training methods being restrictive and costly have become less relevant. One of the challenges faced by teachers is to provide customized learning catering to the needs of every student. As different students have different requirements, even teaching one student is an arduous task as the teacher is challenged to find the right curriculum to meet their requirements.

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The theory of computation is one of the crown jewels of the computer science curriculum. It stretches from the discovery of mathematical problems, such as the halting problem, that cannot be solved by computers, to the most celebrated open problem in computer science today: the P vs. NP question. Since the founding of our discipline by Church and Turing in the 1930s, the theory of computation has addressed some of the most fundamental questions about computers: What does it mean to compute the solution to a problem? Which problems can be solved by computers? Which problems can be solved efficiently, in theory and in practice?