10-Days-Of-DL

• tensorflow 2.0 을 이용한 10일 완성 deep learning
• Ten days complete deep learning using tenorflow 2.0

👉 Requirements

• python 3.6
• tensorflow 2.0 (https://www.tensorflow.org)
• Numpy
• matplotlib
• Anaconda(https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/)
• Jupyter Notebook

💻 Install

See the TensorFlow install guide for the pip package, to enable GPU support, use a Docker container, and build from source.

To install the current release for CPU-only:

$ pip install tensorflow

Use the GPU package for CUDA-enabled GPU cards:

$ pip install tensorflow-gpu

Nightly binaries are available for testing using the tf-nightly and tf-nightly-gpu packages on PyPi.

Try your first TensorFlow program

$ python

>>> import tensorflow as tf
>>> tf.enable_eager_execution()
>>> tf.add(1, 2).numpy()
3
>>> hello = tf.constant('Hello, TensorFlow!')
>>> hello.numpy()
'Hello, TensorFlow!'

For more examples, see the TensorFlow tutorials.

📖 Course

Day1: Machine Learning 기본

• Theory
• Code

Day2: Linear Regression hypothesis & cost

• Theory

Day3: Linear Regression cost 최적화 알고리즘

• Theory
• Linear regression Code

Day4: Multi-variable Linear regression

• Theory
• Multi-variable Linear regression Code

Day5: Logistic Classification & cost function

• Theory
• Logistic Classification Code

Day6: Softmax regression & cost function

• Theory
• Softmax regression Code

Day7: Rate, Overfitting, Regularization, training & test

• Theory 1
• Theory 2
• Training & Evaluationn Code

📚 Resources

• TensorFlow.org
• TensorFlow tutorials
• TensorFlow official models
• TensorFlow examples
• TensorFlow in Practice from Coursera
• TensorFlow blog
• TensorFlow Twitter
• TensorFlow YouTube
• TensorFlow roadmap
• TensorFlow white papers
• TensorBoard visualization toolkit

Learn more about the TensorFlow community and how to contribute.

©️ License

 Copyright 2019 Team Daliy_Learning in BlueCat-Community

 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
 You may obtain a copy of the License at
 
 http://www.apache.org/licenses/LICENSE-2.0

 Unless required by applicable law or agreed to in writing, software
 distributed under the License is distributed on an "AS IS" BASIS,
 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License.