Are you sitting there, eyes glued to the screen, feeling a sudden pang of curiosity to dive into the world of machine learning? Do you envision yourself whipping up some snazzy AI applications or unraveling the mysteries of neural networks? If your answer is an unequivocal “Yes!”, you’ve come to the right place, my friend! TensorFlow, the exceptionally popular deep learning library developed by none other than Google, is here to turn your dreams into reality. And what better way to learn than by exploring some (drumroll, please) TensorFlow online courses?
Now, before you scratch your head and wonder which course you should choose from the seemingly endless options, fret not – we’ve got your back! To uncomplicate your decision-making process, we’ve gone ahead and sifted through the vast sea of online courses to bring you the crème de la crème of TensorFlow offerings. These courses, handpicked by experts, cater to a wide array of learners – from curious beginners to AI-savvy aficionados. So, buckle up and get ready to embark on your TensorFlow adventure with these phenomenal online courses!
Tensorflow Courses – Table of Contents
- TensorFlow Developer Certificate in 2023: Zero to Mastery
- Tensorflow 2.0: Deep Learning and Artificial Intelligence
- Complete Tensorflow 2 and Keras Deep Learning Bootcamp
- Deep Learning Masterclass with TensorFlow 2 Over 20 Projects
- A deep understanding of deep learning (with Python intro)
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TensorFlow Developer Certificate in 2023: Zero to Mastery
Platform:
Udemy
Rating:
4.6 out of 5
Ready to dive into the world of TensorFlow and become a certified expert? Look no further, as this comprehensive online course will transform you from an absolute beginner into a state-of-the-art deep learning neural network pro. Taught by a certified TensorFlow expert, the course is designed to help you pass the TensorFlow Developer Certificate exam, so you can officially join Google’s TensorFlow Certification Network, making your resume stand out and gaining access to a fantastic live online community with over 900,000 students!
Throughout the course, you’ll experience hands-on and project-based learning, covering everything from TensorFlow fundamentals to advanced neural networks, computer vision, natural language processing, and time series forecasting. Not only will you build machine learning models and projects mimicking real-life scenarios, but you’ll also learn from scratch and gain essential skills needed to develop modern deep learning solutions encountered by big tech companies. So, if you’re ready to join the rapidly growing machine learning industry and earn up to $204,000 USD a year as a TensorFlow expert, enroll now and start your journey towards becoming a Google Certified Developer!
Skills you’ll learn in this course:
- Building and training deep learning neural networks with TensorFlow
- Developing skills to diagnose and solve regression and classification problems
- Creating computer vision and convolutional neural networks
- Utilizing transfer learning and fine-tuning pre-trained models
- Preprocessing and handling natural language text for neural networks
- Building and evaluating models with RNNs, LSTMs, GRUs, and CNNs for NLP tasks
- Understanding and applying time series fundamentals in TensorFlow
- Practical implementation through hands-on projects, including Food Vision and SkimLit.
Tensorflow 2.0: Deep Learning and Artificial Intelligence
Platform:
Udemy
Rating:
4.7 out of 5
Welcome to the exciting world of TensorFlow 2.0, Google’s powerful deep learning and artificial intelligence library! This comprehensive course caters to beginners and experts alike, taking you on a journey from basic machine learning models to state-of-the-art concepts. Along the way, you’ll explore major deep learning architectures like Deep Neural Networks, Convolutional Neural Networks (image processing) and Recurrent Neural Networks (sequence data), as you work on exciting projects such as Natural Language Processing (NLP), Recommender Systems, Transfer Learning for Computer Vision, Generative Adversarial Networks (GANs), and a Deep Reinforcement Learning Stock Trading Bot.
Geared towards learning fast, the course offers in-depth sections for those who want to dig deeper into the theory behind the techniques. Advanced TensorFlow topics include deploying a model with TensorFlow Serving and TensorFlow Lite, distributed TensorFlow training with Distribution Strategies, writing custom TensorFlow models, and converting TensorFlow 1.x code to TensorFlow 2.0. The instructor’s primary focus lies in building cool stuff rather than delving into dense theory, so if you’re looking for a hands-on, engaging experience, this is the course for you! With every line of code explained in detail and a welcoming community of learners, you’ll be well on your way to mastering TensorFlow 2.0 in no time.
Skills you’ll learn in this course:
- Deep learning and artificial intelligence concepts
- Working with major deep learning architectures (Deep Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks)
- Natural Language Processing (NLP)
- Building Recommender Systems
- Transfer Learning for Computer Vision
- Developing Generative Adversarial Networks (GANs)
- Implementing Deep Reinforcement Learning (e.g. Stock Trading Bot)
- Time series forecasting and stock predictions
Complete Tensorflow 2 and Keras Deep Learning Bootcamp
Platform:
Udemy
Rating:
4.7 out of 5
In this comprehensive course, you’ll be guided through using Google’s TensorFlow 2 framework to create artificial neural networks for deep learning in an easy-to-understand manner. Focused on leveraging the Keras API (TensorFlow 2.0’s official API) for quick model building, the course covers various application scenarios such as forecasting home prices, classifying medical images, predicting future sales data, and even generating artificial text. Balancing theory and practical implementation, the course offers complete Jupyter notebook guides, reference slides, notes, and exercises to test your skills along the way.
The curriculum covers a wide range of topics, including a crash course on NumPy, Pandas data analysis, and Data Visualization, as well as diving into the basics of Neural Networks, TensorFlow, and Keras Syntax. You’ll also explore advanced topics such as Convolutional Neural Networks, Recurrent Neural Networks, AutoEncoders, and Generative Adversarial Networks (GANs), preparing you to deploy TensorFlow into production. By using Keras, you’ll benefit from the user-friendly API standard for machine learning and TensorFlow 2’s enhancements, like eager execution and scalable input pipelines through tf.data. Join this course and become a deep learning expert today!
Skills you’ll learn in this course:
- Master TensorFlow 2 framework and Keras API
- Forecast future price homes with built models
- Classify medical images with deep learning algorithms
- Create models to predict future sales data
- Generate complete new text artificially
- Understand Neural Network Basics
- Deploy TensorFlow models into production
- Implement Convolutional Neural Networks, Recurrent Neural Networks, AutoEncoders, and GANs.
Deep Learning Masterclass with TensorFlow 2 Over 20 Projects
Platform:
Udemy
Rating:
4.4 out of 5
Deep Learning is a booming field in computer science with wide-ranging applications in areas like Computer Vision, Natural Language Processing, Image Generation, and Signal Processing. This comprehensive course guides you through mastering different concepts using a step-by-step, project-based approach. You’ll be working with popular tools like Tensorflow 2 and Huggingface, diving into everything from simple models like Linear regression and binary classifiers to advanced models such as object detection with YOLO, lyrics generation with GPT2, and image generation with GANs.
Throughout the course, you’ll be learning the basics of Tensorflow, Deep Learning algorithms like Convolutional Neural Networks and Vision Transformers, model evaluation, techniques for mitigating overfitting, and much more. You’ll also dabble in Natural Language Processing, Sentiment Analysis, and Machine Translation. By the end of the course, you’ll have developed the skill sets needed to create modern deep-learning solutions akin to those used by big tech companies. So, if you’re ready to take a major leap in your career, this course by Neuralearn has you covered. And remember, don’t hesitate to ask questions or provide feedback on the course forum to ensure the best learning experience! Enjoy!
Skills you’ll learn in this course:
- Mastering Tensorflow basics and deep learning algorithms like Convolutional Neural Networks and Vision Transformers
- Evaluating Classification Models using metrics like Precision, Recall, Accuracy, and F1-score
- Mitigating overfitting with Data Augmentation techniques
- Implementing advanced Tensorflow concepts like Custom Losses, Metrics, and Training Loops
- Understanding Machine Learning Operations (MLOps) with tools like Weights and Biases
- Developing models for tasks like Malaria detection, Human Emotions Detection, and Object Detection with YOLO
- Deploying models using techniques like Distillation, Onnx format, Quantization, and cloud platforms such as Heroku
- Exploring Natural Language Processing and text generation using Recurrent Neural Networks, Attention Models, Transformers, and pretrained architectures like GPT2 and Deberta
A deep understanding of deep learning (with Python intro)
Platform:
Udemy
Rating:
4.8 out of 5
Looking to dive deep into the world of deep learning? This comprehensive course is designed for those who genuinely want to understand the ins and outs of deep learning, rather than just getting a quick overview. Throughout the course, you will gain flexible, fundamental, and lasting expertise, equipping you with a solid understanding of the concepts that will enable you to learn new topics and trends as they arise in the future. Just a heads up: this course is not for those seeking superficial knowledge from a YouTube video. Instead, it’s for individuals who genuinely want to grasp how and why deep learning works, and how to apply this knowledge to various scenarios.
The course has a lot to offer — from covering theoretical and mathematical aspects to diving into the implementations of deep learning models using Python with the PyTorch library. You’ll also get multiple explanations for concepts like transfer learning, generative modeling, convolutional neural networks, feedforward networks, GANs, and so much more. What’s more, you’ll be able to master Python through an 8+ hour tutorial, learn how to use Google Colab, and participate in numerous exercises and projects that will fortify your deep learning expertise. With clear explanations, interactive Q&A forums and visualizations to help build your intuition, it’s time to dive into the fascinating world of deep learning. So go ahead, check out the course introductory video, and see if this transformative journey is the right fit for you!
Skills you’ll learn in this course:
- Deep understanding of fundamental concepts in deep learning
- Selection and usage of metaparameters like optimizers, normalizations, and learning rates
- Evaluation of deep neural network model performance
- Modification and adaptation of existing models to solve new problems
- Python programming skills
- Implementation of deep learning models using PyTorch library
- Usage of Google Colab for running Python code and simulations
- Transfer learning, generative modeling, and various neural network architectures
In conclusion, investing your time and effort into learning TensorFlow through online courses is a wise decision that can provide significant long-term benefits. Not only can you gain expertise in machine learning and artificial intelligence, but you’ll also be adding a highly sought-after skill to your repertoire, making you more competitive in the job market. Plus, the flexibility and variety offered by online courses allow you to find the ideal learning environment and pace that suits your needs and preferences.
Don’t wait any longer to level up your skills in TensorFlow. Dive into one of these fantastic online courses and explore the exciting world of machine learning and AI. Remember, practice makes perfect. So, start working on projects, engage with the AI community, and share your progress as you learn and grow. Happy coding, and we eagerly await seeing the incredible things you create with your newfound TensorFlow knowledge!