Note: 4.6/5 (106 notes) 28,948 students Welcome to experience "Jetpack 1.0″. Today, we are seeing an increasing number of applications of AI-based solutions across fields like eCommerce Marketing, Personalised Recommendations, Targeted Marketing, Finance Industry, etc. Artificial Intelligence (AI) seemed to be a distant reality for the HR function, until today. Artificial Intelligence (AI) usage for Human Resources (HR) seemed to be a narrative similar to every support function across organizations across India and the world. Welcome to experience "Jetpack 1.0: Artificial Intelligence and Automation in HR" – an incredible topic as part of the series that is created by Digital Marketing Legend "Srinidhi Ranganathan", Mastermind "Saranya Srinidhi" and Marketing Expert "Sai Manoj". "Jetpack 1.0" is going to change the old ideas of following traditional HR processes and functions.
This book was designed around major building blocks of the Python ecosystem that are useful to machine learning projects. There are a lot of things you could learn about Python, from language mechanics to the various libraries. Our goal is to take you straight to developing an intuition for the elements you can use in Python projects with laser-focused tutorials. We designed the tutorials to focus on how to get things done with Python. They give you the tools to both rapidly understand and apply each technique or operation. Each tutorial is designed to take you about one hour to read through and complete, excluding the extensions and further reading. You can choose to work through the lessons one per day, one per week, or at your own pace. I think momentum is critically important, and this book is intended to be read and used, not to sit idle. I would recommend picking a schedule and sticking to it.
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 Ruder.io, 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.
Machine learning is the foundation for predictive modeling and artificial intelligence. If you want to learn about both the underlying concepts and how to get into building models with the most common machine learning tools this path is for you. In this course, you will learn the core principles of machine learning and how to use common tools and frameworks to train, evaluate, and use machine learning models. This course is designed to prepare you for roles that include planning and creating a suitable working environment for data science workloads on Azure. You will learn how to run data experiments and train predictive models. In addition, you will manage, optimize, and deploy machine learning models into production.
Want To Know How to deploy powerful ML solutions on the cloud? This program is designed for the AI & ML professional who wants to excel in Deep learning, Computer vision, Data Mining, computer vision, Image processing, and more using cloud technologies. This program gives you in-depth knowledge on how to use Azure Machine Learning Designer using Microsoft Azure and build AI models. You can also learn the computer vision workloads and custom vision services using Microsoft Azure through this program. Learn essential to advanced topics like image analysis, face service, form recognizer, and optical character recognizer using Microsoft Azure.
The software firm has undergone vivid changes over the last few years. Meanwhile, Machine learning as a service provider (MLaaS) is evolving at a brisk phase. MLaaS has transformed into an integral aspect of managing a business in the digital era. Moreover, Machine Learning as a Service enables a range of tools that embrace Machine learning tools as part of cloud computing services. MLaaS is a sunshade for stockpiling numerous cloud-based manifesto that depends on machine learning tools to offer solutions that could boost Machine Learning teams with pre-processing of the data, straight off predictive analysis for distinct use cases, model training and tuning, and run orchestration.
Welcome to the course on Data Science & Deep Learning for Business 20 Case Studies! This course teaches you how Data Science & Deep Learning can be used to solve real-world business problems and how you can apply these techniques to 20 real-world case studies. Traditional Businesses are hiring Data Scientists in droves, and knowledge of how to apply these techniques in solving their problems will prove to be one of the most valuable skills in the next decade! "I'm only half way through this course, but i have to say WOW. It's so far, a lot better than my Business Analytics MSc I took at UCL. The content is explained better, it's broken down so simply. Some of the Statistical Theory and ML theory lessons are perhaps the best on the internet! "It is pretty different in format, from others.
What is the machine learning lifecycle represent? Automatically learning without being pre-programmed is possible thanks to machine learning. But what exactly is a machine learning system, and how does it work? So, it is classified as a machine learning life cycle. The machine learning life cycle is a cyclical process for producing a successful machine learning initiative.
Machine Learning with AWS is the right place to start if you are a beginner interested in learning useful artificial intelligence (AI) and machine learning skills using Amazon Web Services (AWS), the most popular and powerful cloud platform. You will learn how to use AWS to transform your projects into apps that work at high speed and are highly scalable. From natural language processing (NLP) applications, such as language translation and understanding news articles and other text sources, to creating chatbots with both voice and text interfaces, you will learn all that there is to know about using AWS to your advantage. You will also understand how to process huge numbers of images fast and create machine learning models. By the end of this course, you will have developed the skills you need to efficiently use AWS in your machine learning and artificial intelligence projects.
Are you a data scientist or AI practitioner who wants to understand cloud platforms? Are you a data scientist or AI practitioner who has worked on Azure or AWS and curious to know how ML activities can be done on GCP? If yes, this course is for you. This course will help you to understand the concepts of the cloud. In the interest of the wider audience, this course is designed for both beginners and advanced AI practitioners.