DeepLearning.AI TensorFlow Developer

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Below are the top discussions from Reddit that mention this online Coursera professional certificate from DeepLearning.AI.

TensorFlow is one of the most in-demand and popular open-source deep learning frameworks available today.

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

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Taught by
Laurence Moroney
Instructor
and 10 more instructors

Offered by
DeepLearning.AI

This professional-certificate includes these 4 courses.

Reddit Posts and Comments

2 posts • 50 mentions • top 19 shown below

r/deeplearning • post
17 points • lopespm
Course 3 of the deeplearning.ai TensorFlow Specialization is now available: TensorFlow in Practice | Coursera
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/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/tensorflow • post
9 points • TomerHorowitz
About to take the TensorFlow certification

Hi guys, I am about to take the TensorFlow certification in the following days and I was wondering if some of you could provide some details on how the certification is handled, what are the questions like, how hard it was, etc

Please spare me your links for reports of other people, I wanna hear your personal experience with the certification.

and for those of you who have passed, how did you study for it? I personally just finished the Coursera TensorFlow in Practice Specialization which I found to be interesting.

I am looking forward to hearing from you guys!

UPDATE: please check this suggestion I have made.

r/learnmachinelearning • comment
2 points • StoneCypher

Thank you. Do you mean this?

r/learnmachinelearning • comment
2 points • rtayek

i have completed a few dozen coursera courses on ml and data science. yes, ng's courses are very good. the newer ones a bit better than the older ones. also if you are a beginner, this series https://www.coursera.org/specializations/tensorflow-in-practice and some others with Laurence Moroney will be easier.

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.

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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.

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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/datascience • comment
1 points • ghnreigns

Just to check that if the exam is quite similar in terms of difficulty as compared to the exercises in the Coursera's TensorFlow in Practice Specialization .

Also, do I need to know commands like !wget to get data from the Tensorflow Datasets? Thanks!

r/artificial • comment
1 points • katy531

Yes, this is indeed a sought after course.

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/OMSA • comment
1 points • colonel_raptor

I completely agree. I took an ML course in college and had ML work come my way. Applying ML without DEEP math isn't too bad - just look at Hands on ML with SciKitLearn, TensorFlow and Keras. This is all about utilizing algorithms that have already been built for you. Same thing with this Coursera course by Andrew Ng. I'm not an ML engineer - I just use this stuff on the job based on what I've been taught in these books. Not that hard without an ML background, just need a really solid programming background to do it well.

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/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 • comment
1 points • Sagyam

Coursera is giving lot's of good courses with certifications for free right now if you have a student email ID. All of these are in coursera

  1. Deep Learning Specialization from deeplearning.ai
  2. TensorFlow in Practice Specialization from deeplearning.ai
  3. Natural Language Processing Specialization from deeplearning.ai
  4. Getting Started with AWS Machine Learning from AWS (There's no coding assingments and it teaches you about AWS APIs for ML/DL task)
  5. And obviously Andrew Ng Stanford Machine Learning Course

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

r/BITSPilani • comment
1 points • throwaway573412

IT placements require DSA, OOP
There are many courses/competitive-sites to learn from, just start with one and you are good to go. Many find Stanford algorithms course the most comfortable.
Extras:
(using algo in everyday life) https://www.goodreads.com/book/show/25666050-algorithms-to-live-by
(Think like a programmer) https://www.youtube.com/channel/UCLEMTlEe5RE04EoULMHWEEQ

​

Machine Learning and Foundations of Data Sci aren't taught well in Pilani. If you're gonna do Data Sci, prefer focusing on more practical stuff than focusing on theory.
Extras:

Try these (practical)
https://www.coursera.org/specializations/tensorflow-in-practice
https://www.kaggle.com/

Extras:
https://www.fast.ai/
AI podcasts: https://www.youtube.com/user/lexfridman
Python plays Grand Theft Auto V : https://www.youtube.com/watch?v=ks4MPfMq8aQ&list=PLQVvvaa0QuDeETZEOy4VdocT7TOjfSA8a

And as always, don't get overwhelmed by too much stuff, take it slow and steady.