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

Day4: Multi-variable Linear regression

Day5: Logistic Classification & cost function

Day6: Softmax regression & cost function

Day7: Rate, Overfitting, Regularization, training & test

📚 Resources

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.

BlueCat-Community/10-Days-Of-DL