Top 10 Best Online Tensorflow Courses

Minh Gia 3 0 Error

A software package called TensorFlow is used to create and train complex deep neural networks and other machine learning applications. In the current digital ... read more...

  1. On top of the Best Online Tensorflow Courses, this course is for you if you are interested in learning more about TensorFlow, Machine Learning, Neural Networks, Deep Learning, Deep Neural Networks (DNN), and Convolution Neural Networks (CNN) with a thorough knowledge. Details are provided for each topic. Concepts are built gradually and methodically. Instead of racing through a slide, the teacher took more than ten minutes to discuss it. This should make it easier for you to grasp and stay on top of the information being delivered.


    The goal of the practical examples is to familiarize you with some TensorFlow 2 features or other knowledge that may come in handy if you ever need to manage a large-scale, intricate neural network task on your own. Downloadable samples are offered for your use. If you want to better grasp the course, view the first two videos.


    There is no one profession that should focus on machine learning. A very potent technique that may help you tackle some problems that you might not otherwise know how to address is machine learning, which works in conjunction with neural networks. Try this course out and see if it helps you understand some of the issues you are working on better.


    Requirements:

    • Some knowledge in algebra and calculus
    • Gmail account to use Google Colab and Google Drive
    • Basic programming knowledge using Python 3
    • All codes are provided for you to download
    • No software needed to install on your computer

    Who this course is for:

    • Beginner
    • People from a diverse range of professions may find this knowledge useful in their own profession


    Course Rating: 4.9/5
    Enroll here:
    https://www.udemy.com/course/machine-learning-and-deep-learning-using-tensorflow/

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  2. Tensorflow is the subject of several tutorials and courses. In contrast, certain practical skills are hard to come by in this vast collection of deep learning resources, and acquiring them would take a lot of time. So you're the target audience for this Tensorflow course! The student will be introduced to the fundamentals of executing a classification project using deep neural networks before learning how to create a dataset for professional deep learning projects at an industrial level. The learner will discover how to use Tensorflow and Keras to create a face recognition software.


    This course covers that gap by offering a number of hands-on projects and practical lectures in which the teacher presents the best practices that deep learning practitioners need to be aware of in order to carry out deep learning projects. The detailed explanations provided by the hands-on projects cover every step of the deep learning process, from data collection through data loading, preprocessing, training, and assessment.

    Requirements:

    • Understand the basic concepts of machine learning (recommended, but not required)
    • Be familiar with Python programming language and data structures (Numpy, Pandas)
    • Understand the basic concepts of neural networks (recommended, but not required)

    Who this course is for:

    • Someone who learned the concepts of deep learning, but want to master the practical aspects of deep learning projects
    • PhD and Master students doing thesis on deep learning
    • Any enthusiast about artificial intelligence and deep learning
    • Computer vision practitioners
    • Anyone who would like to learn about best practices in deep learning
    • Anyone who like to quickly start with deep learning without having a background in it


    Course Rating: 4.7/5
    Enroll here:
    https://www.udemy.com/course/deep-learning-in-practice-i/

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  3. Are you interested in websites and JavaScript apps that use machine learning? Then you should take this course! This is the guide you've been seeking for to master machine learning with JavaScript in 2022. By the end of the course, you will have advanced machine learning skills that you can put on your resume; it doesn't only cover the fundamentals. Learn TensorFlow.js from scratch to become a master and join the revolution. A specialized group of software engineers that are enthusiastic about utilizing JavaScript with Machine Learning created this course.


    With the aid of detailed laboratories and exams, the instructor will walk you through challenging concepts in a way that is both practical and effective. Every illustration builds upon the one before it to reinforce learning in small, manageable chunks. All of TensorFlow's advantages are available to you through machine learning with TensorFlow.js, but Python is not required. Web-based examples, attractive visuals, and unique website elements are used to illustrate this.


    Requirements:

    • Javascript basics
    • Some high school math

    Who this course is for:

    • Anyone who wants to start using machine learning in their apps and websites using Javascript


    Course Rating: 4.7/5
    Enroll here:
    https://www.udemy.com/course/machine-learning-in-javascript-with-tensorflow-js/

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  4. The transition from concept to code and from model to publishing is simple with TensorFlow 2. It has a number of features that make it possible to define and train cutting-edge models without compromising speed or performance. This course will show you how to build artificial neural networks for deep learning using Google's newest TensorFlow 2 framework! This course aims to provide you with an accessible introduction to the complexity of Google's TensorFlow 2 framework.


    It will concentrate on comprehending the most recent TensorFlow improvements and using the Keras API (the official TensorFlow 2.0 API) to rapidly and readily create models. In this course, the instructor will create models that predict future home prices, categorize medical photos, anticipate future sales data, artificially create entirely new language, and much more! This course's entire jupyter notebook code instructions, easily accessible slides, and notes are all meant to strike a balance between theory and practical application. There are many of activities throughout the course to put your newly learned abilities to the test.


    Requirements:

    • Know how to code in Python
    • Some math basics such as derivatives

    Who this course is for:

    • Python developers interested in learning about TensorFlow 2 for deep learning and artificial intelligence


    Course Rating: 4.7/5
    Enroll here:
    https://www.udemy.com/course/complete-tensorflow-2-and-keras-deep-learning-bootcamp/

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  5. Google's deep learning and artificial intelligence library is called Tensorflow. The most widely used deep learning library in the world, Tensorflow, was created by Google, whose parent firm Alphabet just overtook Apple as the richest business in terms of cash. It is the preferred library for many businesses engaged in AI and machine learning.


    In other words, you must be familiar with Tensorflow if you wish to perform deep learning. You will begin this course with some very fundamental machine learning models before moving on to cutting-edge ideas. All of the key deep learning architectures, including Deep Neural Networks, Convolutional Neural Networks (for image processing), and Recurrent Neural Networks, will be covered along the way (sequence data).


    In addition to brand-new applications that have never been done before, such as time series forecasting and market forecasts, you will still learn how to update your old code to utilize Tensorflow 2.0. This course has "in-depth" portions if you want to delve a bit further into the theory, but it is also aimed for those who want to learn quickly (like what is a loss function, and what are the different types of gradient descent approaches).


    Requirements:

    • Know how to code in Python and Numpy
    • For the theoretical parts (optional), understand derivatives and probability

    Who this course is for:

    • Beginners to advanced students who want to learn about deep learning and AI in Tensorflow 2.0


    Course Rating: 4.7/5
    Enroll here:
    https://www.udemy.com/course/deep-learning-tensorflow-2/

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  6. Let's enroll in a course being taught by a TensorFlow certified expert and join a live online community of more than 600,000 students. With the help of this course, you may advance from being a complete novice with TensorFlow to building cutting-edge deep learning neural networks and joining Google's TensorFlow Certification Network. According to figures from 2022, TensorFlow specialists may make up to $204,000 USD year, with the typical pay sitting around $148,000 USD.


    You may enter the booming machine learning market and further your career as a top-paid TensorFlow developer by completing this certificate exam, which is recognized by Google. In addition, if you pass the test, you will gain access to Google's TensorFlow Developer Network, where employers may locate you. This course's objective is to provide you with all the knowledge and abilities you'll need to ace the test and get your Google TensorFlow Certification, which you can use to stand out on LinkedIn, Github, and other social networking sites.


    Requirements:

    • Mac / Windows / Linux - all operating systems work with this course!
    • No previous TensorFlow knowledge required

    Who this course is for:

    • Students, developers, and data scientists who want to demonstrate practical machine learning skills through the building and training of models using TensorFlow
    • Anyone looking to expand their knowledge when it comes to AI, Machine Learning and Deep Learning
    • Anyone looking to master building ML models with the latest version of TensorFlow


    Course Rating: 4.7/5
    Enroll here:
    https://www.udemy.com/course/tensorflow-developer-certificate-machine-learning-zero-to-mastery/

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    • As one of the Best Online Tensorflow Courses, the purpose of this course is to address practical computer vision challenges as you examine fundamental Deep Learning techniques. The instructor will go through fundamental Machine Learning concepts including Neural Networks, Multi-class classification, Logistic Regression, and Linear Regression.


      You must be interested in learning Deep Learning For Computer Vision and applying your knowledge to real-world issues if you've made it this far. You could already be familiar with machine learning, computer vision, or deep learning, or you might be learning about it for the first time. Regardless of where you started, you will be an expert with a lot of practical experience with TensorFlow after completing this course.


      Using the information from this course, you will work on a variety of tasks such as object detection, image production, object counting, object identification, illness detection, picture segmentation, and more. Your comments and inquiries on the forum will help this course get better.


      Requirements:

      • Basic Math
      • No Programming experience

      Who this course is for:

      • Beginner Python Developers curious about Applying Deep Learning for Computer vision
      • Deep Learning for Computer vision Practitioners who want gain a mastery of how things work under the hood
      • Anyone who wants to master deep learning fundamentals and also practice deep learning for computer vision using best practices in TensorFlow.
      • Computer Vision practitioners who want to learn how state of art computer vision models are built and trained using deep learning.


      Course Rating: 4.6/5
      Enroll here:
      https://www.udemy.com/course/master-deep-learning-for-computer-vision-with-tensorflow-2/

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    • Researchers in AI, machine learning, and data science each have a unique set of talents. But what is that unique characteristic they share? They are all deep learning experts. It's clear how fascinating deep learning is. The course is business-focused and provides you practical experience using Deep Learning with TensorFlow to enhance corporate performance, but the main objective is career advancement.


      The teacher doesn't just skim the surface either; after all, learning isn't dubbed "skin-deep" for nothing. He covers every aspect of the subject, from the mathematics behind the algorithms to the most recent initialization techniques, and much more. Without application, theory is worthless, isn't it? He thus provides you with several opportunity to use this notion.


      Implement cutting-edge improvements, experiment with TensorFlow, or even create your own algorithm and train it! Wow, it will look fantastic on your CV. When you finish a distinguished 365 Careers course, you also receive a certificate that employers may use to confirm your completion, which is relevant to resumes.


      Requirements:

      • Some basic Python programming skills
      • You’ll need to install Anaconda
      • All software and data used in the course are free

      Who this course is for:

      • Aspiring data scientists
      • People interested in Machine Learning, Deep Learning, Business, and Artificial Intelligence,
      • Anyone who wants to learn how to code and build machine and deep learning algorithms from scratch


      Course Rating: 4.6/5
      Enroll here:
      https://www.udemy.com/course/machine-learning-with-tensorflow-for-business-intelligence/

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    • This is also one of the Best Online Tensorflow Courses. TensorFlow was initially developed by scientists and engineers on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural network research, but the system is sufficiently general to be applicable in a wide range of other domains as well. This course will show you how to build deep learning artificial neural networks using Google's TensorFlow framework.


      This course attempts to provide you with an accessible introduction to the complexity of Google's TensorFlow framework. Other tutorials and courses frequently avoid using plain TensorFlow in favor of abstractions that give the user less control. The course finally acts as a comprehensive manual for utilizing the TensorFlow framework as intended while demonstrating the newest deep learning methods! This course's entire jupyter notebook code instructions, easily accessible slides, and notes are all meant to strike a balance between theory and practical application. Let's master TensorFlow right now!


      Requirements:

      • Some knowledge of programming (preferably Python)
      • Some basic knowledge of math (mean, standard deviation, etc..)

      Who this course is for:

      • Python students eager to learn the latest Deep Learning Techniques with TensorFlow


      Course Rating: 4.4/5
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      nroll here: https://www.udemy.com/course/complete-guide-to-tensorflow-for-deep-learning-with-python/

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    • Recently, TensorFlow 2.0 was launched, and it included a number of enhancements that made the process of creating and maintaining models easier. By deconstructing numerous complicated ideas, it improves people's comprehension from an educational standpoint. From the perspective of the industry, models are more simpler to comprehend, produce, and maintain. One of the most rapidly expanding subfields in artificial intelligence is deep learning. It has been demonstrated in recent years that Deep Learning models, even the most basic ones, are capable of solving extremely challenging and complicated problems.


      People are unleashing Deep Learning's strength and promise for product enhancements now that the initial hype has, in part, subsided. The course is designed to cover every topic, starting with neural network modeling and training and ending with putting it into use. Although it is more common these days for Android or iOS applications to have a Deep Learning model, neural networks are quite energy and resource intensive. The TensorFlow Lite library can be used in this situation. You will discover how to adapt and optimize any neural network to function on a mobile device in Section 12 of the course.


      Requirements:

      • Some math basics like knowing what is a differentiation or a gradient
      • Python basics

      Who this course is for:

      • Deep Learning Engineers who want to learn Tensorflow 2.0
      • Artificial Intelligence Engineers who want to expand their Deep Learning stack skills
      • Computer Scientists who want to enter the exciting area of Deep Learning and Artificial Intelligence
      • Data Scientists who want to take their AI Skills to the next level
      • AI experts who want to expand on the field of applications
      • Python Developers who want to enter the exciting area of Deep Learning and Artificial Intelligence
      • Engineers who work in technology and automation
      • Businessmen and companies who want to get ahead of the game
      • Students in tech-related programs who want to pursue a career in Data Science, Machine Learning, or
      • Artificial Intelligence
      • Anyone passionate about Artificial Intelligence


      Course Rating: 4.3/5
      Enroll here:
      https://www.udemy.com/course/tensorflow-2/

      https://www.udemy.com/course/tensorflow-2/
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