Big Data Analytics in IOT domain

Deep learning is a new and advanced area of machine learning that can be used in many different fields. It has shown promise in many areas, such as computer vision, drug discovery, and predicting the stock market. Many books and articles on deep learning cover its algorithms, theories, and applications. Also, many researchers and people who aren't in computer science or related fields are interested in learning about deep learning architectures and using them in their projects because they can solve different kinds of problems by using different kinds of data.This course covers the fundamentals of artificial neural networks and deep learning before focusing on generative adversarial networks and their applications, complete with coding examples to help you understand the concepts. This course is for people who are new to machine learning and deep learning and want to learn how to use Python, TensorFlow, and Keras to implement deep learning algorithms, especially GAN algorithms.The course is broken up into seven chapters. The first one is about the basics of machine learning, and the last one is about CycleGAN. Each chapter includes quizzes and assignments to put students' knowledge to the test. It also has a solution for each project.I think that the information in this course will be well received by undergraduate and graduate students, researchers in deep learning, and practitioners in academia and business around the world.

هذا الكورس مناسب لثلاثة اختصاصات صناعية حسب كورسات سيمنز سترينالصيانةالبرمجةالخدماتيمكنك من خلال هذا الكورس التعامل باحترافية مع سيماتك منجر حتى وان كان مستواك متوسطا في مجال سيمنز فهذا الكورس يعطيك دفعة للامام في هذا البرنامج متعدد المهام والنوافذ!الكورس مقسم الى 5 اقسام رئيسية والعديد من الدروس الفرعيةانشاء مشروعك الاولالتصميمالاعداداتالبرمجةكشف الاخطاءهاردوير

Learn the basics of Github and Git. In this video lecture series I have tried to explain you the basic theory about the Github platform. Also you will get to know about what is the meaning of a repository and how do we create a repository. I have covered not only the practical applications but also the basic theory about the repositories as well as aimed to give some hands on experience on creating the repository.Next you will learn the basics of READMEs. I have tried to explain you what are the different types of READMEs and what are their importance. P.S. one should always make a README while starting a repository.Learn how to add the code files to your GitHub repository. I have discussed 3 ways by which you can add the files. In this video lecture I have tried to explain you the CLI tool, Github desktop and the browser GUI In this video I have shared some awesome tricks with you to work like a pro on GitHub and also earn rewards for making improvements as a developer.I have given emphasis on explaining the pros and cons of each method that we discussed in video lectures so that you can choose the best one for yourself.I have also given apt knowledge by which you can host your projects using Github's free hosting.Then in the further videos we'll be discussing about the open source and what is the importance of the open source contributions in the tech community.Learn how can we search a repository and use the code present in it. I have tried to explain you how one can make a pull request and contribute to the open source.I have also made an attempt to go through all major elements on GitHub's website and have explained the use of each element.In the last video I have also shared some awesome tricks with you to work like a pro on GitHub and also earn rewards for making improvements as a developer.

Master Azure Fundamentals with Confidence!Prepare for the AZ-900 Microsoft Azure Fundamentals exam with six expertly crafted timed practice tests. Each exam includes 50 unique and original questions, ensuring 300 high-quality practice questions in total.Updated for the latest AZ-900 exam changes.Covers all domains:Cloud Concepts (25–30%)Azure Architecture Services (35–40%)Azure Management Governance (30–35%)If you’re unsure whether you're ready for the AZ-900 exam, these realistic practice tests will assess your knowledge. Identify weak areas, improve your understanding, and boost your confidence before the real exam.Each question is carefully designed to reflect the real exam format, ensuring you get the most authentic test experiencepossible. Unlike generic practice tests found online, these questions are 100% original and updated based on Microsoft's latest guidelines.Azure remains the fastest-growing cloud platform, and demand for cloud professionals is higher than ever. Whether you’re starting your career, switching to cloud computing, or upskilling, this certification is a valuable first step.Beyond passing the exam, mastering Azure fundamentals can open doors to high-paying cloud jobs in IT, development, and security. Having an Azure certification on your resume helps demonstrate your expertise to employers and stand out in job applications.Enroll today and take the first step toward cloud success!

The "Optimization with Genetic Algorithms: Hands-on Python" course is a comprehensive and practical guide to understanding and implementing genetic algorithms for solving various optimization problems. Genetic algorithms, inspired by the principles of natural evolution, are powerful techniques for finding optimal solutions in multiple domains.In this course, you will learn the fundamental concepts of genetic algorithms and their applications in optimization. Starting from the basics, you will explore the principles of selection, crossover, and mutation that drive the evolution process. You will understand how to represent problem solutions as chromosomes, apply genetic operators to generate offspring, and evaluate the fitness of individuals.With a hands-on approach, you will dive into implementing genetic algorithms using Python programming language. Through a real-world problem project, you will gain proficiency in designing and optimizing genetic algorithms for real-world scenarios. You will learn how to define appropriate fitness functions, set up population structures, control algorithm parameters, and handle constraints in optimization problems.Throughout the course, you will explore different variations of genetic algorithms, including elitism, to enhance the optimization process. By the end of the course, you will have a strong foundation in genetic algorithms and be equipped with the skills to apply them to a wide range of optimization problems. You will be able to implement efficient and effective genetic algorithms in Python, analyze their performance, and make informed decisions for parameter tuning and problem-specific customization.Whether you are a student, programmer, researcher, or professional seeking advanced optimization techniques, this course will empower you to solve complex problems using genetic algorithms and unleash the power of optimization in your projects and applications.

Looking for an perfect job interview preparation? Searching in the web brings you only partial information? Congrats! You found what you are looking for!Do you have a job interview related to data science, python programming, Big Data or in the financial industry in general? If you can answer this question with a yes, you are in the absolute perfect place.This course provides you 6 different job interview preparation. As we have deep insides in different industries, we know exactly what matters contentwise.We made some surveys to find out what fields are connected to each other and on top of that we found out which topics are important.It is clear to everyone, that job interviews differ based on your experience. If you are a Senior Software Developer you know exactly what matters. The practice tests in this course brings you up to date in the different topics covered in this course. Our focus is on the knowledge. The tests inlcudes questions from beginner level up to advanced level. We do not cover behavioral or pychological topics, we boost your know-how, not your behaviour in this course, as every job interview will be helt in a different way. But the content will be almost the same per knowledge area.As you now know what you can expect, lets go a bit deeper in the content of this course. The following big topics will challenge you:PythonData ScienceBusiness IntelligenceFinancial AnalysisBig dataHadoopThis is a bundle of related topics. The chances are very high that you will work more than one of this subject areas at once. As a Data Scientist you should know how to do programming using Python these days.There are 6 practice tests, one for each topic mentioned above.