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  • Tensorflow

Results for "tensorflow"


  • D

    DeepLearning.AI

    DeepLearning.AI TensorFlow Developer

    Skills you'll gain: Tensorflow, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Computer Vision, Model Evaluation, Transfer Learning, Image Analysis, Keras (Neural Network Library), Natural Language Processing, Model Training, Time Series Analysis and Forecasting, Deep Learning, Embeddings, Fine-tuning, Artificial Neural Networks, Applied Machine Learning, Generative AI, Classification Algorithms, Forecasting, Machine Learning

    ★ 4.7 (25K) · Intermediate · Professional Certificate · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • I

    IBM

    IBM Deep Learning with PyTorch, Keras and Tensorflow

    Skills you'll gain: PyTorch (Machine Learning Library), Transfer Learning, Model Evaluation, Fine-tuning, Vision Transformer (ViT), Keras (Neural Network Library), Deep Learning, Convolutional Neural Networks, Reinforcement Learning, Model Optimization, Autoencoders, Generative AI, Model Training, Unsupervised Learning, Tensorflow, Artificial Neural Networks, Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), Statistical Methods, Logistic Regression

    ★ 4.5 (4.2K) · Intermediate · Professional Certificate · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: AI skills
    AI skills
    Category: Credit offered
    Credit offered
  • D

    DeepLearning.AI

    Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

    Skills you'll gain: Tensorflow, Computer Vision, Model Evaluation, Image Analysis, Convolutional Neural Networks, Keras (Neural Network Library), Deep Learning, Artificial Neural Networks, Model Training, Applied Machine Learning, Artificial Intelligence, Data Preprocessing, Machine Learning

    ★ 4.8 (20K) · Intermediate · Course · 1 - 4 Weeks

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • I

    Imperial College London

    TensorFlow 2 for Deep Learning

    Skills you'll gain: Tensorflow, Generative AI, Recurrent Neural Networks (RNNs), Autoencoders, Generative Model Architectures, Data Pipelines, Keras (Neural Network Library), Model Evaluation, Deep Learning, Image Analysis, Model Training, Bayesian Network, Transfer Learning, Convolutional Neural Networks, Computer Programming, Model Optimization, Data Validation, Applied Machine Learning, Bayesian Statistics, Supervised Learning

    ★ 4.8 (722) · Intermediate · Specialization · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • I

    IBM

    IBM AI Engineering

    Skills you'll gain: Prompt Engineering, Apache Spark, PyTorch (Machine Learning Library), Large Language Modeling, Retrieval-Augmented Generation, Transfer Learning, Model Evaluation, Computer Vision, Unsupervised Learning, Generative Model Architectures, Generative AI, PySpark, Prompt Engineering Tools, Vision Transformer (ViT), Keras (Neural Network Library), Vector Databases, Fine-tuning, Machine Learning, Python Programming, Data Science

    ★ 4.6 (22K) · Intermediate · Professional Certificate · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Build toward a degree
    Build toward a degree
  • D

    DeepLearning.AI

    TensorFlow: Advanced Techniques

    Skills you'll gain: Generative Adversarial Networks (GANs), Autoencoders, Generative AI, Tensorflow, Computer Vision, Image Analysis, Transfer Learning, Convolutional Neural Networks, Generative Model Architectures, Fine-tuning, Deep Learning, Keras (Neural Network Library), Model Training, Model Optimization, Applied Machine Learning, Artificial Neural Networks, Classification Algorithms, Model Evaluation, Distributed Computing, Visualization (Computer Graphics)

    ★ 4.8 (1.7K) · Intermediate · Specialization · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered

What brings you to Coursera today?

  • P

    Packt

    Deep Learning with TensorFlow

    Skills you'll gain: Recurrent Neural Networks (RNNs), Transfer Learning, Model Optimization, Tensorflow, Artificial Neural Networks, Applied Machine Learning, Embeddings, Keras (Neural Network Library), Deep Learning, Time Series Analysis and Forecasting, Fine-tuning, Image Analysis, Classification Algorithms, Convolutional Neural Networks, Natural Language Processing, Computer Vision, Model Training, Forecasting, Machine Learning, Text Mining

    ★ 4.7 (6) · Intermediate · Specialization · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • G

    Google Cloud

    Learning TensorFlow: the Hello World of Machine Learning

    Skills you'll gain: Tensorflow, Google Cloud Platform, Scripting, Data-Driven Decision-Making, Model Training, Applied Machine Learning, Machine Learning Methods, Artificial Neural Networks, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Cloud Computing, Development Environment

    ★ 4 (20) · Beginner · Project · Less Than 2 Hours

    Category: Credit offered
    Credit offered
  • C

    Coursera

    Build & Optimize TensorFlow ML Workflows

    Skills you'll gain: Tensorflow, Model Optimization, Keras (Neural Network Library), Model Training, MLOps (Machine Learning Operations), Data Pipelines, Performance Tuning, Data Preprocessing

    Intermediate · Course · 1 - 4 Weeks

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • I

    IBM

    Deep Learning with Keras and Tensorflow

    Skills you'll gain: Keras (Neural Network Library), Convolutional Neural Networks, Reinforcement Learning, Deep Learning, Model Optimization, Autoencoders, Generative AI, Unsupervised Learning, Tensorflow, Generative Adversarial Networks (GANs), Generative Model Architectures, Transfer Learning, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Model Training, Time Series Analysis and Forecasting

    ★ 4.4 (1K) · Intermediate · Course · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • I

    Imperial College London

    Getting started with TensorFlow 2

    Skills you'll gain: Tensorflow, Keras (Neural Network Library), Model Evaluation, Deep Learning, Image Analysis, Model Training, Convolutional Neural Networks, Computer Programming, Model Optimization, Data Validation, Applied Machine Learning, Supervised Learning, Computer Vision, Artificial Neural Networks, Data Persistence

    ★ 4.9 (582) · Intermediate · Course · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • C

    Coursera

    Tweet Emotion Recognition with TensorFlow

    Skills you'll gain: Recurrent Neural Networks (RNNs), Tensorflow, Model Optimization, Python Programming, Model Training, Natural Language Processing, Data Preprocessing, Applied Machine Learning, Artificial Neural Networks, Text Mining, Machine Learning Algorithms, Deep Learning, Classification Algorithms, Machine Learning

    ★ 4.5 (174) · Intermediate · Guided Project · Less Than 2 Hours

    Category: Free
    Free
    Category: Credit offered
    Credit offered
1234…26

In summary, here are 10 of our most popular tensorflow courses

  • DeepLearning.AI TensorFlow Developer: DeepLearning.AI
  • IBM Deep Learning with PyTorch, Keras and Tensorflow: IBM
  • Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning: DeepLearning.AI
  • TensorFlow 2 for Deep Learning: Imperial College London
  • IBM AI Engineering: IBM
  • TensorFlow: Advanced Techniques: DeepLearning.AI
  • Deep Learning with TensorFlow: Packt
  • Learning TensorFlow: the Hello World of Machine Learning: Google Cloud
  • Build & Optimize TensorFlow ML Workflows: Coursera
  • Deep Learning with Keras and Tensorflow: IBM

Skills you can learn in Machine Learning

Python Programming (33)
Tensorflow (32)
Deep Learning (30)
Artificial Neural Network (24)
Big Data (18)
Statistical Classification (17)
Reinforcement Learning (13)
Algebra (10)
Bayesian (10)
Linear Algebra (10)
Linear Regression (9)
Numpy (9)

Frequently Asked Questions about Tensorflow

TensorFlow is an open-source machine learning framework developed by Google that allows developers to create complex neural networks and machine learning models. It is important because it provides a flexible and comprehensive ecosystem for building and deploying machine learning applications. TensorFlow supports various tasks, from simple linear regression to advanced deep learning applications, making it a versatile tool for data scientists and developers alike.‎

With skills in TensorFlow, you can pursue various job roles in the tech industry. Common positions include Machine Learning Engineer, Data Scientist, AI Researcher, and Software Developer specializing in AI applications. These roles often involve designing and implementing machine learning models, analyzing data, and developing algorithms that can learn from and make predictions based on data.‎

To effectively learn TensorFlow, you should focus on several key skills. First, a solid understanding of Python programming is essential, as TensorFlow is primarily used with this language. Additionally, knowledge of machine learning concepts, linear algebra, and statistics will greatly enhance your ability to work with TensorFlow. Familiarity with neural networks and deep learning principles is also crucial, as these are fundamental to many TensorFlow applications.‎

There are many excellent online courses available for learning TensorFlow. Notable options include the DeepLearning.AI TensorFlow Developer Professional Certificate, which provides a comprehensive introduction to TensorFlow and its applications. Another great choice is the Deep Learning with TensorFlow Specialization, which covers various aspects of deep learning using TensorFlow.‎

Yes. You can start learning TensorFlow on Coursera for free in two ways:

  1. Preview the first module of many TensorFloww courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

If you want to keep learning, earn a certificate in TensorFlow, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

To learn TensorFlow, start by exploring introductory courses that cover the basics of machine learning and TensorFlow itself. Engage with hands-on projects to apply what you learn in real-world scenarios. Utilize online resources, such as tutorials and documentation, to deepen your understanding. Joining community forums can also provide support and insights from other learners and professionals.‎

Typical topics covered in TensorFlow courses include the fundamentals of machine learning, building and training neural networks, working with TensorFlow APIs, and deploying models. Advanced courses may explore specialized areas such as computer vision, natural language processing, and reinforcement learning, providing a well-rounded education in machine learning.‎

For training and upskilling employees, the IBM Deep Learning with PyTorch, Keras and Tensorflow Professional Certificate is an excellent choice. It equips learners with practical skills in deep learning and TensorFlow, making it suitable for organizations looking to enhance their workforce's capabilities in AI and machine learning.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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