TensorFlow in Practice

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Below are the top discussions from Reddit that mention this online Coursera specialization from deeplearning.ai.

Discover the tools software developers use to build scalable AI-powered algorithms in TensorFlow, a popular open-source machine learning framework.

Computer Vision Convolutional Neural Network Machine Learning Natural Language Processing Tensorflow Inductive Transfer Augmentation Dropouts Tokenization RNNs Forecasting Time Series

Accessible for free. Completion certificates are offered.

Affiliate disclosure: Please use the blue and green buttons to visit Coursera if you plan on enrolling in a course. Commissions Reddsera receives from using these links will keep this site online and ad-free. Reddsera will not receive commissions if you only use course links found in the below Reddit discussions.

Taught by
Laurence Moroney
AI Advocate

Offered by
deeplearning.ai

This specialization includes these 4 courses.

Reddit Posts and Comments

4 posts • 38 mentions • top 18 shown below

r/deeplearning • post
17 points • lopespm
Course 3 of the deeplearning.ai TensorFlow Specialization is now available: TensorFlow in Practice | Coursera
r/learnmachinelearning • comment
4 points • sarabkohli29

You could actually start with a specialization. Tensorflow in practice taught by Laurence Moroney, AI Advocate at Google Brain.

In this four-course Specialization, you’ll explore exciting opportunities for AI applications. Begin by developing an understanding of how to build and train neural networks. Improve a network’s performance using convolutions as you train it to identify real-world images. You’ll teach machines to understand, analyze, and respond to human speech with natural language processing systems. Learn to process text, represent sentences as vectors, and input data to a neural network. You’ll even train an AI to create original poetry!

https://www.coursera.org/specializations/tensorflow-in-practice

r/artificial • post
19 points • tlalco
How does the Udacity and Coursera TF 2 courses compare?

Im wondering what each course is good for.

​

https://www.udacity.com/course/intro-to-tensorflow-for-deep-learning--ud187

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https://www.coursera.org/specializations/tensorflow-in-practice

r/tensorflow • post
14 points • tlalco
How does the Udacity and Coursera TF 2 courses compare?

Im wondering what each course is good for.

https://www.udacity.com/course/intro-to-tensorflow-for-deep-learning--ud187

https://www.coursera.org/specializations/tensorflow-in-practice

r/tensorflow • comment
4 points • davidshen84

https://www.coursera.org/specializations/deep-learning https://www.coursera.org/specializations/tensorflow-in-practice

r/tensorflow • comment
6 points • suryaavala

Assuming that you are not new to programming in Python or to Deep Learning concepts, I reckon the best place to start would be tutorials/guides on the Tensorflow website.

​

If you need more guidance along the process, maybe take a look at this Tensorflow Specialization on Coursera made by deeplearning.ai in conjunction with Google Brain.

​

There are so many not so good resources on the internet for Tensorflow (and ML/AI in general), I would suggest you be wary of them and stick to more reliable/official sources.

r/MachineLearning • post
1 points • lopespm
[N] Course 3 of the deeplearning.ai TensorFlow Specialization is now available: TensorFlow in Practice | Coursera
r/artificial • comment
1 points • katy531

Yes, this is indeed a sought after course.

r/tensorflow • post
1 points • stillanoobummkay
Free/open source alternatives to TensorFlow in Practice Specialization

Coursera offers TensorFlow in Practice Specialization but only if you sign up for the paid version of coursera.

So, I'm wondering if there is an equivalent (or almost equivalent) free/open source version or a collection of works that is comparable?

r/learnmachinelearning • post
1 points • godsavetheducks
Course recommendation (NLP)

I have a interest and a small work background in NLP. I just finished the tensorflow in practice specialization by deeplearning.ai (https://www.coursera.org/specializations/tensorflow-in-practice) Are there any similar courses for NLP?

r/learnmachinelearning • comment
3 points • ItisAhmad

Yes, I am the author. This program will get you good understanding of all the basics of Machine & Deep Learning. After completing this program I suggest you 2 things and then you'll be able to get job.

1)Good grip on TensorFlow or Pytorch:

For this, you can take TensorFlow in Practice specialization by deeplearning.ai at coursera.

For PyTorch take the course mentioned in a blog or you can take courses from fast.ai

2)Self Projects:

Pick a problem you know or you can think of and start making its solution with machine learning or deep learning from all the things you have learned. you will fail in this project as if it is your first project, but with hard work, you will get better. then do another project and after 2 projects you will easily be able to get a job in the market.

r/tensorflow • comment
1 points • shravan_rcb

Found this today:

https://www.adhiraiyan.org/DeepLearningWithTensorflow.html

Course:

https://www.coursera.org/specializations/tensorflow-in-practice

Hope it helps.

r/learnmachinelearning • comment
1 points • kanishkarora89

https://www.coursera.org/specializations/tensorflow-in-practice

Its from deeplearning.ai .

(You can apply for financial aid also)

r/learnpython • comment
1 points • my_password_is______

in order


https://www.coursera.org/specializations/deep-learning

Deep Learning Specialization

5 course specialization

  • Neural Networks and Deep Learning
  • Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
  • Structuring Machine Learning Projects
  • Convolutional Neural Networks
  • Sequence Models

In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory, but also see how it is applied in industry. You will practice all these ideas in Python and in TensorFlow, which we will teach.


https://www.coursera.org/specializations/tensorflow-in-practice

TensorFlow in Practice Specialization

4 course specialization

  • Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
  • Convolutional Neural Networks in TensorFlow
  • Natural Language Processing in TensorFlow
  • Sequences, Time Series and Prediction

In this four-course Specialization, you’ll explore exciting opportunities for AI applications. Begin by developing an understanding of how to build and train neural networks. Improve a network’s performance using convolutions as you train it to identify real-world images. You’ll teach machines to understand, analyze, and respond to human speech with natural language processing systems. Learn to process text, represent sentences as vectors, and input data to a neural network. You’ll even train an AI to create original poetry!


https://www.coursera.org/specializations/ai-for-medicine

AI for Medicine Specialization

3 course specialization

  • AI for Medical Diagnosis
  • AI for Medical Prognosis
  • AI For Medical Treatment

  • In Course 1, you will create convolutional neural network image classification and segmentation models to make diagnoses of lung and brain disorders.

  • In Course 2, you will build risk models and survival estimators for heart disease using statistical methods and a random forest predictor to determine patient prognosis.
  • In Course 3, you will build a treatment effect predictor, apply model interpretation techniques and use natural language processing to extract information from radiology reports.

You don't need to be an AI expert, but a working knowledge of deep neural networks, particularly convolutional networks, and proficiency in Python programming at an intermediate level will be essential. If you are relatively new to machine learning or neural networks, we recommend that you first take the Deep Learning Specialization, offered by deeplearning.ai and taught by Andrew Ng.

r/datascience • post
1 points • fmarm
Passed TensorFlow Developer Certification

Hi,

I have passed this week the TensorFlow Developer Certificate from Google. I could not find a lot of feedback here about people taking it so I am writing this post hoping it will help people who want to take it.

The exam contains 5 problems to solve, part of the code is already written and you need to complete it. It can last up to 5 hours, you need to upload your ID/Passport and take a picture using your webcam at the beginning, but no one is going to monitor what you do during those 5 hours. You do not need to book your exam beforehand, you can just pay and start right away. There is no restriction on what you can access to during the exam.

I strongly recommend you to take Coursera's TensorFlow in Practice Specialization as the questions in the exam are similar to the exercises you can find in this course. I had previous experience with TensorFlow but anyone with a decent knowledge of Deep Learning and finishes the specialization should be capable of taking the exam.

I would say the big drawback of this exam is the fact you need to take it in Pycharm on your own laptop. I suggest you do the exercises from the Specialization using Pycharm if you haven't used it before (I didn't and lost time in the exam trying to get basic stuff working in Pycharm). I don't have GPU on my laptop and also lost time while waiting for training to be done (never more than \~10mins each time but it adds up), so if you can get GPU go for it! In my opinion it would have make more sense to do the exam in Google Colab...

Last advice: for multiple questions the source comes from TensorFlow Datasets, spend some time understanding the structure of the objects you get as a result from load_data , it was not clear for me (and not very well documented either!), that's time saved during the exam.

I would be happy to answer other questions if you have some!

r/artificial • comment
1 points • Stippes

You got an interesting challenge at hand!
While it can be interesting for your participants to do the same task as an AI throughout the day, I think there might be more actual lessons they could take out of it.
-You could provide them some images and let them make their own classifier with https://teachablemachine.withgoogle.com/

-You can teach them about the dangers of misclassification - let them come up with a rule based on which to put people into prison (interesting because similar methods are being used in the states) and then let them see how easily they will misjudge people based on some criteria (I admit, this idea doesn't convince me yet :D )

-As a kind of hands-on example, I like the Tensorflow in practive specialization (https://www.coursera.org/specializations/tensorflow-in-practice). They very easily show how to program an AI in a Google Colab environment. Your participants could even run the notebooks on their own laptops.

But, I guess to give you a better recommendation, you need to let us know what the overall aim of this training is. Just to introduce them to AI?

r/learnmachinelearning • post
1 points • mallasahaj
Suggestions, please

After tons of research, here is the list of courses that I think are good for me. I want to make my own AI projects to help society benefit from it.

  1. Algorithm about machine learning
  2. Python course
  3. Mathematics for machine learning
  4. Applied data science with python
  5. Deep learning
  6. TensorFlow in practice
  7. Advance Machine learning

After these, I'm planning to do some of my own ML projects. Can you suggest to me if the order of the courses is good or suggestions on which course should I apply or not?

Thanks!

r/computervision • comment
1 points • enes81

I also wanna start a CV course in this time. I couldn't decide yet but here is a list of courses I found.

https://www.youtube.com/watch?v=njKP3FqW3Sk&list=PLtBw6njQRU-rwp5__7C0oIVt26ZgjG9NI

https://www.youtube.com/watch?v=0VH1Lim8gL8&list=PLrAXtmErZgOeiKm4sgNOknGvNjby9efdf

https://www.youtube.com/watch?v=aircAruvnKk&list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi

https://www.youtube.com/playlist?list=PLE-BQwvVGf8HOvwXPgtDfWoxd4Cc6ghiP

https://developers.google.com/machine-learning/crash-course

https://www.edx.org/course/computer-vision-and-image-analysis-2

https://www.udacity.com/course/computer-vision-nanodegree--nd891?cjevent=f3f072406c4911ea80b202e60a180512

https://www.udacity.com/course/introduction-to-computer-vision--ud810

https://www.coursera.org/specializations/robotics

https://www.coursera.org/learn/introduction-tensorflow

https://www.coursera.org/specializations/tensorflow-in-practice

https://www.coursera.org/specializations/deep-learning

https://www.coursera.org/learn/computer-vision-basics