Will TensorFlow 2.0 support common Machine Learning libraries stated below?
With the exciting new features of TensorFlow 2.0, may I know if TensorFlow 2.0 will still support the common machine learning techniques as stated below?
- Linear Regression
- Logistic Regression
- K-Means Clustering
K-Nearest Neighbors
Random Forest
Naive Bayes- Support Vector Machine
Thank you very much for your time and clarification in advance.
tensorflow
asked Nov 27 '18 at 23:12
Admond LeeAdmond Lee
11
add a comment |
With the exciting new features of TensorFlow 2.0, may I know if TensorFlow 2.0 will still support the common machine learning techniques as stated below?
- Linear Regression
- Logistic Regression
- K-Means Clustering
K-Nearest Neighbors
Random Forest
Naive Bayes- Support Vector Machine
Thank you very much for your time and clarification in advance.
tensorflow
asked Nov 27 '18 at 23:12
Admond LeeAdmond Lee
11
There are some words about compatibility in the original announcement, but I don't think you'll get anything more specific before an actual release.tf.contribas such will not exist, and subproject maintainers will be responsible for compatibility ("we will work with the respective owners on detailed migration plans", "we are looking for owners/maintainers for a number of projects currently in tf.contrib"). I'd assume everything officially supported now will be there, but no guarantees abouttf.contrib.
– jdehesa
Nov 28 '18 at 11:29
add a comment |
With the exciting new features of TensorFlow 2.0, may I know if TensorFlow 2.0 will still support the common machine learning techniques as stated below?
- Linear Regression
- Logistic Regression
- K-Means Clustering
K-Nearest Neighbors
Random Forest
Naive Bayes- Support Vector Machine
Thank you very much for your time and clarification in advance.
tensorflow
asked Nov 27 '18 at 23:12
Admond LeeAdmond Lee
11
With the exciting new features of TensorFlow 2.0, may I know if TensorFlow 2.0 will still support the common machine learning techniques as stated below?
- Linear Regression
- Logistic Regression
- K-Means Clustering
K-Nearest Neighbors
Random Forest
Naive Bayes- Support Vector Machine
Thank you very much for your time and clarification in advance.
tensorflow
tensorflow
asked Nov 27 '18 at 23:12
Admond LeeAdmond Lee
11
asked Nov 27 '18 at 23:12
Admond LeeAdmond Lee
11
asked Nov 27 '18 at 23:12
Admond LeeAdmond Lee
11
asked Nov 27 '18 at 23:12
Admond LeeAdmond Lee
11
asked Nov 27 '18 at 23:12
Admond LeeAdmond Lee
11
11
There are some words about compatibility in the original announcement, but I don't think you'll get anything more specific before an actual release.tf.contribas such will not exist, and subproject maintainers will be responsible for compatibility ("we will work with the respective owners on detailed migration plans", "we are looking for owners/maintainers for a number of projects currently in tf.contrib"). I'd assume everything officially supported now will be there, but no guarantees abouttf.contrib.
– jdehesa
Nov 28 '18 at 11:29
add a comment |
There are some words about compatibility in the original announcement, but I don't think you'll get anything more specific before an actual release.tf.contribas such will not exist, and subproject maintainers will be responsible for compatibility ("we will work with the respective owners on detailed migration plans", "we are looking for owners/maintainers for a number of projects currently in tf.contrib"). I'd assume everything officially supported now will be there, but no guarantees abouttf.contrib.
– jdehesa
Nov 28 '18 at 11:29
There are some words about compatibility in the original announcement, but I don't think you'll get anything more specific before an actual release.
tf.contrib as such will not exist, and subproject maintainers will be responsible for compatibility ("we will work with the respective owners on detailed migration plans", "we are looking for owners/maintainers for a number of projects currently in tf.contrib"). I'd assume everything officially supported now will be there, but no guarantees about tf.contrib.– jdehesa
Nov 28 '18 at 11:29
There are some words about compatibility in the original announcement, but I don't think you'll get anything more specific before an actual release.
tf.contrib as such will not exist, and subproject maintainers will be responsible for compatibility ("we will work with the respective owners on detailed migration plans", "we are looking for owners/maintainers for a number of projects currently in tf.contrib"). I'd assume everything officially supported now will be there, but no guarantees about tf.contrib.– jdehesa
Nov 28 '18 at 11:29
add a comment |
1 Answer
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The models that you mention above will still definitely be supported in TensorFlow 2.0 as part of tf.estimator. If you are using a symbol in TensorFlow 1.x that is currently housed in tf.contrib, it will either be deprecated, transitioned to the tensorflow/addons repo, or moved into the core TF 2.0 API.
You can check out the RFCs below for more detailed changes:
- TensorFlow Namespaces
- Sunsetting
tf.contrib
- Move from
tf.contribtotensorflow/addons
answered Feb 11 at 19:47
dynamicwebpaigedynamicwebpaige
627
add a comment |
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1 Answer
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1 Answer
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active
oldest
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votes
The models that you mention above will still definitely be supported in TensorFlow 2.0 as part of tf.estimator. If you are using a symbol in TensorFlow 1.x that is currently housed in tf.contrib, it will either be deprecated, transitioned to the tensorflow/addons repo, or moved into the core TF 2.0 API.
You can check out the RFCs below for more detailed changes:
- TensorFlow Namespaces
- Sunsetting
tf.contrib
- Move from
tf.contribtotensorflow/addons
answered Feb 11 at 19:47
dynamicwebpaigedynamicwebpaige
627
add a comment |
The models that you mention above will still definitely be supported in TensorFlow 2.0 as part of tf.estimator. If you are using a symbol in TensorFlow 1.x that is currently housed in tf.contrib, it will either be deprecated, transitioned to the tensorflow/addons repo, or moved into the core TF 2.0 API.
You can check out the RFCs below for more detailed changes:
- TensorFlow Namespaces
- Sunsetting
tf.contrib
- Move from
tf.contribtotensorflow/addons
answered Feb 11 at 19:47
dynamicwebpaigedynamicwebpaige
627
add a comment |
The models that you mention above will still definitely be supported in TensorFlow 2.0 as part of tf.estimator. If you are using a symbol in TensorFlow 1.x that is currently housed in tf.contrib, it will either be deprecated, transitioned to the tensorflow/addons repo, or moved into the core TF 2.0 API.
You can check out the RFCs below for more detailed changes:
- TensorFlow Namespaces
- Sunsetting
tf.contrib
- Move from
tf.contribtotensorflow/addons
answered Feb 11 at 19:47
dynamicwebpaigedynamicwebpaige
627
The models that you mention above will still definitely be supported in TensorFlow 2.0 as part of tf.estimator. If you are using a symbol in TensorFlow 1.x that is currently housed in tf.contrib, it will either be deprecated, transitioned to the tensorflow/addons repo, or moved into the core TF 2.0 API.
You can check out the RFCs below for more detailed changes:
- TensorFlow Namespaces
- Sunsetting
tf.contrib
- Move from
tf.contribtotensorflow/addons
answered Feb 11 at 19:47
dynamicwebpaigedynamicwebpaige
627
answered Feb 11 at 19:47
dynamicwebpaigedynamicwebpaige
627
answered Feb 11 at 19:47
dynamicwebpaigedynamicwebpaige
627
answered Feb 11 at 19:47
dynamicwebpaigedynamicwebpaige
627
627
add a comment |
add a comment |
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There are some words about compatibility in the original announcement, but I don't think you'll get anything more specific before an actual release.
tf.contribas such will not exist, and subproject maintainers will be responsible for compatibility ("we will work with the respective owners on detailed migration plans", "we are looking for owners/maintainers for a number of projects currently in tf.contrib"). I'd assume everything officially supported now will be there, but no guarantees abouttf.contrib.– jdehesa
Nov 28 '18 at 11:29