tensorflow-101 | learn code with tensorflow | Machine Learning library
kandi X-RAY | tensorflow-101 Summary
kandi X-RAY | tensorflow-101 Summary
tensorflow-101 is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow, Generative adversarial networks applications. tensorflow-101 has no vulnerabilities and it has medium support. However tensorflow-101 has 25 bugs and it build file is not available. You can download it from GitHub.
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learn code with tensorflow
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License
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Support
tensorflow-101 has a medium active ecosystem.
It has 1124 star(s) with 573 fork(s). There are 87 watchers for this library.
It had no major release in the last 6 months.
There are 10 open issues and 8 have been closed. On average issues are closed in 36 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of tensorflow-101 is current.
Quality
tensorflow-101 has 25 bugs (1 blocker, 0 critical, 5 major, 19 minor) and 554 code smells.
Security
tensorflow-101 has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
tensorflow-101 code analysis shows 0 unresolved vulnerabilities.
There are 30 security hotspots that need review.
License
tensorflow-101 does not have a standard license declared.
Check the repository for any license declaration and review the terms closely.
Without a license, all rights are reserved, and you cannot use the library in your applications.
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tensorflow-101 releases are not available. You will need to build from source code and install.
tensorflow-101 has no build file. You will be need to create the build yourself to build the component from source.
tensorflow-101 saves you 7088 person hours of effort in developing the same functionality from scratch.
It has 14673 lines of code, 618 functions and 134 files.
It has high code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed tensorflow-101 and discovered the below as its top functions. This is intended to give you an instant insight into tensorflow-101 implemented functionality, and help decide if they suit your requirements.
- Deploy a model
- Slimoser for variables
- Add summaries for gradients
- Device name
- Create data from src and target features
- Read src_line
- Finds the similarity between two filenames
- Inception resnet v2
- A block of 8x
- Train the model
- Process a directory tree
- Configures the optimizer
- Get preprocessing function
- Build the graph
- Make a vocabulary from a file
- Compute the accuracy
- Return data sets for training
- Inception v1
- Generate a batch of data
- Runs a prediction
- Configures the learning rate decay
- Validate the training
- Visit a call node
- Inception V2
- Train the graph
- Inception V4
Get all kandi verified functions for this library.
tensorflow-101 Key Features
No Key Features are available at this moment for tensorflow-101.
tensorflow-101 Examples and Code Snippets
Tensorflow 101
Jupyter Notebook
Lines of Code : 2
License : No License
Lines of Code : 2License : No License
Copy$ pip install -r requirements.txt
$ jupyter notebook
Community Discussions
Trending Discussions on tensorflow-101
QUESTION
my pandas and seaborn comands not responding
Asked 2021-Mar-10 at 17:30
import pandas as pd
dataFrame = pd.read_excel("C:/Users/****/desktop/python folder/tensorflow/sheet.xlsx")
import seaborn as sbn import matplotlib.pyplot as plt
sbn.pairplot(dataFrame)
Output is: PS C:\Users \ -----\Desktop\python folder> & C:/Users/------/AppData/Local/Programs/Python/Python39/python.exe "c:/Users/-----/Desktop/python folder/tensorflow/tensorflow-101.py" ...ANSWER
Answered 2021-Mar-10 at 17:30For your problem, try this.
QUESTION
Tensorflow rnn: name 'seq2seq' is not defined
Asked 2017-Apr-12 at 10:41
I am trying this notebook: https://github.com/sjchoi86/Tensorflow-101/blob/master/notebooks/char_rnn_sample_tutorial.ipynb
I have a problem with this line In[6]:
...ANSWER
Answered 2017-Apr-12 at 10:41Because seq2seq has been moved to tf.contrib.legacy_seq2seq. You should change this line to:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install tensorflow-101
You can download it from GitHub.
You can use tensorflow-101 like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use tensorflow-101 like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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