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16 Neutral

Sobre wheesung

  • Cumpleaños 02/02/1996

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  1. Lo que aprenderás: Understand the fundamentals of linear algebra, a ubiquitous approach for solving for unknowns within high-dimensional spaces. Manipulate tensors using the most important Python tensor libraries: NumPy, TensorFlow, and PyTorch Possess an in-depth understanding of matrices, including their properties, key classes, and critical ML operations Develop a geometric intuition of what’s going on beneath the hood of ML and deep learning algorithms. Be able to more intimately grasp the details of cutting-edge machine learning papers Requisitos: All code demos will be in Python so experience with it or another object-oriented programming language would be helpful for following along with the hands-on examples. Familiarity with secondary school-level mathematics will make the class easier to follow along with. If you are comfortable dealing with quantitative information -- such as understanding charts and rearranging simple equations -- then you should be well-prepared to follow along with all of the mathematics. Descripción To be a good data scientist, you need to know how to use data science and machine learning libraries and algorithms, such as NumPy, TensorFlow and PyTorch, to solve whichever problem you have at hand. To be an excellent data scientist, you need to know how those libraries and algorithms work. This is where our course "Machine Learning & Data Science Foundations Masterclass" comes in. Led by deep learning guru Dr. Jon Krohn, this first entry in the Machine Learning Foundations series will give you the basics of the mathematics such as linear algebra, matrices and tensor manipulation, that operate behind the most important Python libraries and machine learning and data science algorithms. The first step in your journey into becoming an excellent data scientist is broken down as follows: Section 1: Linear Algebra Data Structures Section 2: Tensor Operations Section 3: Matrix Properties Section 4: Eigenvectors and Eigenvalues Section 5: Matrix Operations for Machine Learning (Note that, as this is initially being offered as a free course, Udemy limits us to two hours of videos so we only get halfway through Section 2. For a sneak preview of what's to come in the remaining sections, check out the course's code repository in GitHub -- a link is provided in the videos.) Throughout each of the sections, you'll find plenty of hands-on assignments and practical exercises to get your math game up to speed! Are you ready to become an excellent data scientist? Enroll now! See you in the classroom. ¿Para quién es este curso? You use high-level software libraries (e.g., scikit-learn, Keras, TensorFlow) to train or deploy machine learning algorithms, and would now like to understand the fundamentals underlying the abstractions, enabling you to expand your capabilities You’re a software developer who would like to develop a firm foundation for the deployment of machine learning algorithms into production systems You’re a data scientist who would like to reinforce your understanding of the subjects at the core of your professional discipline You’re a data analyst or A.I. enthusiast who would like to become a data scientist or data/ML engineer, and so you’re keen to deeply understand the field you’re entering from the ground up (very wise of you!) Responder a cualquier contenido con "gracias", "bueno", "genial" o algo por el estilo se considera spam (incluye las frases que contengan esas palabras). Si siente la necesidad de expresar gratitud, use sus votos positivos o agradézcalos a través de mensaje privado. EVITE SER SANCIONADO. [Hidden Content]
  2. CURSO EN INGLÉS Lo que aprenderás: Design custom forms to easily and efficiently collect information Set up data filters and validations to better phrase questions Interpret & analyze collected responses Transform ordinary forms to quizzes for educational use Distribute forms to any audience through multiple ways Requisitos: Google account Willingness to learn Descripción Welcome to The Complete Google Forms Course. This course will teach you to understand how to design, share, and analyze questionnaires and quizzes created on the Google application Google Forms. Google Forms is a free survey tool that allows you to easily and efficiently collect information. It is used in both professional and personal settings, whether it is for collecting time availability from your employees or for gathering t-shirt sizes for a family vacation shirt. It supports various types of questions and allows for validation options to control data entry. Although it has a fairly simple user interface, it offers many advantages and can perform a multitude of tasks. As a complete Google Forms course, this course will start with the foundation and design aspects. The lessons from this section include understanding how to add questions, utilizing response validations, customizing headers, and more. In addition, there are a couple of quick wins scattered across the sections to provide more tips on how to use this application to its fullest potential. The second section of this course goes over how to view and analyze the received form responses. With Google Forms’ powerful data analysis, this application is a go-to tool for many businesses, organizations, and classrooms. Since you have full configuration over the form, you are able to decide exactly how you want the form to look and what information you want it to collect. Google Forms is highly recommended by many for educational purposes. The third section goes over how to transform an ordinary form into a self-grading quiz with just one button. It also talks about how to add answer feedback and create a point system to help alleviate the stress of administering and grading. Google Forms is a powerful application that allows you to create surveys to easily collect an ambulance of diverse types of information. This course will also show you how to send out forms to collect data from the comforts of your own home. Some of the many things that you can make on Google Forms include: Job application, time off request, customer feedback Contact information, event RSVP Exit ticket, quizzes, course evaluation, etc Enroll to learn how to use Google Forms to create surveys and quizzes! ¿Para quién es este curso? Anyone interested in learning Google Forms Responder a cualquier contenido con "gracias", "bueno", "genial" o algo por el estilo se considera spam (incluye las frases que contengan esas palabras). Si siente la necesidad de expresar gratitud, use sus votos positivos o agradézcalos a través de mensaje privado. EVITE SER SANCIONADO. [Hidden Content]
  3. CURSO EN INGLÉS Lo que aprenderás: Create presentable data visualizations with Python Learn how to analyze data with Python Make interactive data visualizations using the Plotly module Learn how to create plots from your data using Matplotlib, and Seaborn Analyze data using the Pandas library to create and structure data Analyze data using the NumPy library to create and manipulate arrays Use the Jupyter Notebook Environment Descripción This course will provide an introduction to the fundamental Python tools for effectively analyzing and visualizing data. You will have a strong foundation in the field of Data Science! You will gain an understanding of how to utilize Python in conjunction with scientific computing and graphing libraries to analyze data, and make presentable data visualizations. This course is designed for both beginners with some basic programming experience or experienced developers looking to explore the world of Data Science! In this course you will: - Learn how to create and analyze data arrays using the NumPy package - Learn how to use the Pandas library to create and analyze data sets - Learn how to use Matplotlib, and Seaborn to create professional, eye-catching data visualizations - Learn how to use Plotly to create interactive charts and plots You will also get lifetime access to all the video lectures, detailed code notebooks for every lecture, as well as the ability to reach out to me anytime for directed inquiries and discussions. ¿Para quién es este curso? Anyone interested in learning more about Python, Data Science, or Data Visualizations Developers interested in learning how to Analyze and Visualize data with Python Anyone interested about the rapidly expanding world of Data Science! Udemy Link: Responder a cualquier contenido con "gracias", "bueno", "genial" o algo por el estilo se considera spam (incluye las frases que contengan esas palabras). Si siente la necesidad de expresar gratitud, use sus votos positivos o agradézcalos a través de mensaje privado. EVITE SER SANCIONADO. Responding to any content with "thank you", "good", "great" or something like that is considered spam (include phrases that contain those words). If you feel the need to express gratitude, use your positive votes or thank them through a private message. AVOID BE PUNISHED. [Hidden Content]
  4. El que actualmente utilizo es Avira Antivirus, me va bien, Antes, en una PC antigua no utilizaba ninguna, tampoco tenía problemas.
  5. >Matemática, muy bien aprendida para saber de que hablan en sí los que dictan los cursos. >Álgebra Lineal. >Algoritmos, redes neuronales, Q-learning, Clustering, K-means. >Estadística muy bien aprendidas. Y más cosas, en pl4tzi existe un curso llamado 'Fundamentos de Matemática para Machine L.' en cual tiene enlaces a cursos relacionados y fundamentales del tema. En la universidad difícilmente te enseñarán.
  6. El canal de 'NoCopyrightSong' en YouTube te puede servir, o tal vez buscando en inglés en duckduckgo puedes encontrar.
  7. wheesung

    Fans del Anime

    Claro que sí, el anime me sirve para relajarme un poco, lamentablemente los animes actuales no cumplen mucho con mis expectativas. Los animes que actualmente ando siguiendo son: >JoJo's >Deca-Dence >Re:Zero S02 >The God of HighSchool >SAO Alicization S02
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