Get a comprehensive, in-depth introduction to the core Python language with this hands-on book. Based on author Mark Lutz's popular training course, this updated fifth edition will help you quickly write efficient, high-quality code with Python. It's an ideal way to begin, whether you're new to programming or a professional developer versed in other languages. Complete with quizzes, exercises, and helpful illustrations, this easy-to-follow, self-paced tutorial gets you started with both Python 2.7 and 3.3-- the latest releases in the 3.X and 2.X lines--plus all other releases in common use today. You'll also learn some advanced language features that recently have become more common in Python code.

TensorFlow, the most popular and widely used machine learning framework, has made it possible for almost anyone to develop machine learning solutions with ease. With TensorFlow (TF) 2.0, you'll explore a revamped framework structure, offering a wide variety of new features aimed at improving productivity and ease of use for developers. This book covers machine learning with a focus on developing neural network-based solutions. You'll start by getting familiar with the concepts and techniques required to build solutions to deep learning problems. As you advance, you'll learn how to create classifiers, build object detection and semantic segmentation networks, train generative models, and speed up the development process using TF 2.0 tools such as TensorFlow Datasets and TensorFlow Hub.

Lead a team and help develop next-generation AI technologies used by millions. Duolingo AI Research is a nimble and rapidly-growing team that has already revolutionized language learning for more than 300 million people around the world.

When you begin to study machine learning, you'll soon realize the importance of KDnuggets. This tutorial is an invaluable resource for delving into data science statistics, as it covers core topics like sampling distribution and the central limit theorem.

We provide IT training based on corporates standards that helps students to be prepare for industries. Sky Infotech offers best Machine Learning training in Delhi, Sky Infotech is one of the best result-oriented Best Machine Learning Training in Delhi, offers best practically, experimental knowledge in Machine Learning training in Delhi. At Sky Infotech Machine Learning training is conducted by 6 years of experience in managing real-time projects. Sky Infotech Delhi, is providing basic and advanced level of Machine Learning Training with live projects with 100% job placement assistance with top industries. Here, in Sky Infotech's laboratory are well-structured for Machine Learning training in Delhiwhere contenders learn the career-oriented skills to uphold the career path.

In a classroom in rural Maharashtra, students stare at a screen as it reads out their English textbook. The teacher occasionally clicks on a word for its Marathi translation -- the primary language of most students at the school -- or shows them a picture to make them understand a word. This method of learning has started to significantly improve the quality of English education in Maharashtra's government schools. Sanjay Gupta, Chief Executive Officer of EnglishHelper, which created the technology platform, the company developed it after researching the most efficient way to learn a new language. "The challenge is to get exposure to language as a student. This is a multisensory, repetition-based platform which won't confuse the student," he says.

Google's TensorFlow framework is the current leading software for implementing and experimenting with the algorithms that power AI and machine learning. We will embark on this journey by quickly wrapping up some important fundamental concepts, followed by a focus on TensorFlow to complete tasks in computer vision and natural language processing. You will be introduced to some important tips and tricks necessary for enhancing the efficiency of our models. We will highlight how TensorFlow is used in an advanced environment and brush through some of the unique concepts at the cutting edge of practical AI. If you want to develop a solid foundation on using TensorFlow and continue your journey into advancing the state of the art in AI to create your own smart machine learning solutions, this course is for you.

The world of technology is rapidly changing, and one must adapt to it quickly to survive in the race of'survival of the fittest'. The Department of EEE has a team of postgraduate students from the Indian Institute of Technology (IIT) Guwahati, along with their faculty members are developing an Artificial Intelligence-enabled Chatbot named "ALBELA" to teach and support the first-year students of Electrical & Electronics Engineering (EEE). ALBELA is capable of addressing the queries and doubts that each of the approximately 850 students pursuing EEE at the Indian Institute of Technology (IIT) may have and can even scan and convert documents, PDFs or Word and provide results relevant to the query asked. "We have been working on its development since the last 7 months with a team of dedicated 7 research scholars of the department. Earlier we did the trial runs of the Chatbot and started using from this academic session onwards. The response from the students has been overwhelming and we hope that this will become the new normal shortly. Prof. Rohit Sinha, Head EEE Department, and the team IBM have extended their continuous support for this activity."

Deep reinforcement learning(DRL) has been at the center of some of the biggest breakthroughs of artificial intelligence(AI) in the last few years. However, despite all its progress, DRL methods remain incredibly difficult to apply in mainstream solutions given the lack of tooling and libraries. Consequently, DRL remains mostly a research activity that hasn't seen a lot of adoption into real world machine learning solutions. Addressing that problem requires better tools and frameworks. Among the current generation of artificial intelligence(AI) leaders, DeepMind stands alone as the company that has done the most to advance DRL research and development. Recently, the Alphabet subsidiary has been releasing a series of new open source technologies that can help to streamline the adoption of DRL methods.

Automatic analysis of teacher and student interactions could be very important to improve the quality of teaching and student engagement. However, despite some recent progress in utilizing multimodal data for teaching and learning analytics, a thorough analysis of a rich multimodal dataset coming for a complex real learning environment has yet to be done. To bridge this gap, we present a large-scale MUlti-modal Teaching and Learning Analytics (MUTLA) dataset. This dataset includes time-synchronized multimodal data records of students (learning logs, videos, EEG brainwaves) as they work in various subjects from Squirrel AI Learning System (SAIL) to solve problems of varying difficulty levels. The dataset resources include user records from the learner records store of SAIL, brainwave data collected by EEG headset devices, and video data captured by web cameras while students worked in the SAIL products. Our hope is that by analyzing real-world student learning activities, facial expressions, and brainwave patterns, researchers can better predict engagement, which can then be used to improve adaptive learning selection and student learning outcomes. An additional goal is to provide a dataset gathered from the real-world educational activities versus those from controlled lab environments to benefit educational learning community.