Update to TF 2.0.0 (from nightly) and update other libraries

requirements.txt

@@ -1,8 +1,8 @@
 # First make sure to update pip:
-#     $ sudo pip install --upgrade pip
+#     $ sudo python3 -m pip install --upgrade pip
 #
 # Then you probably want to work in a virtualenv (optional):
-#     $ sudo pip install --upgrade virtualenv
+#     $ sudo python3 -m pip install --upgrade virtualenv
 # Or if you prefer you can install virtualenv using your favorite packaging
 # system. E.g., in Ubuntu:
 #     $ sudo apt-get update && sudo apt-get install virtualenv
@@ -13,11 +13,9 @@
 #
 # Next, optionally uncomment the OpenAI gym lines (see below).
 # If you do, make sure to install the dependencies first.
-# If you are interested in xgboost for high performance Gradient Boosting, you
-# should uncomment the xgboost line (used in the ensemble learning notebook).
 #
 # Then install these requirements:
-#     $ pip install --upgrade -r requirements.txt
+#     $ python3 -m pip install --upgrade -r requirements.txt
 #
 # Finally, start jupyter:
 #     $ jupyter notebook
@@ -26,17 +24,17 @@
 
 ##### Core scientific packages
 jupyter==1.0.0
-matplotlib==3.0.3
-numpy==1.16.2
-pandas==0.24.1
-scipy==1.1.0
+matplotlib==3.1.1
+numpy==1.17.2
+pandas==0.25.1
+scipy==1.3.1
 
 
 ##### Machine Learning packages
-scikit-learn==0.20.3
+scikit-learn==0.20.4
 
 # Optional: the XGBoost library is only used in the ensemble learning chapter.
-xgboost==0.82
+xgboost==0.90
 
 
 ##### TensorFlow-related packages
@@ -46,36 +44,35 @@ xgboost==0.82
 # you must install CUDA, cuDNN and more: see tensorflow.org for the detailed
 # installation instructions.
 
-tf-nightly-2.0-preview
-#tf-nightly-gpu-2.0-preview
+tensorflow==2.0.0
+#tensorflow-gpu==2.0.0
 
-#tensorboard
-tb-nightly
+tensorboard==2.0.0
 
-#tensorflow-datasets
-tfds-nightly
+tensorflow-datasets==1.2.0
 
-tensorflow-hub
+tensorflow-hub==0.6.0
 
 # Optional: only used in chapter 13.
-#tensorflow-transform==0.13.0
+tfx==0.14.0
 
 # Optional: only used in chapter 16.
-# At the present (April 2019) the TF Addons library is only available on Linux
-# So uncomment this line if you are using Linux.
-#tensorflow-addons
+#tensorflow-addons==0.6.0
 
 # Optional: the TF Agents library is only needed in chapter 18
 tf-agents-nightly
 
 # Optional: the TF Serving API library is just needed for chapter 19.
-tensorflow-serving-api
+tensorflow-serving-api==1.14.0
 
 
 ##### Image manipulation
-imageio==2.5.0
-Pillow==5.4.1
-scikit-image==0.14.2
+imageio==2.6.0
+Pillow==6.2.0
+scikit-image==0.15.0
+graphviz==0.10.1
+pygraphviz==1.3
+pydot==1.4.1
 
 
 ##### Reinforcement Learning library
@@ -83,7 +80,7 @@ scikit-image==0.14.2
 # OpenAI gym is only needed in chapter 18.
 # There are a few dependencies you need to install first, check out:
 # https://github.com/openai/gym#installing-everything
-gym[atari]==0.10.9
+gym[atari]==0.15.3
 
 
 ##### Additional utilities
@@ -93,19 +90,18 @@ joblib==0.13.2
 
 # May be useful with Pandas for complex "where" clauses (e.g., Pandas
 # tutorial).
-numexpr==2.6.9
+numexpr==2.7.0
 
 # Optional: these libraries can be useful in chapter 3, exercise 4.
 nltk==3.4.5
-urlextract==0.9
+urlextract==0.13.0
 
 # Needed in chapter 19.
 requests==2.22.0
 
 # Optional: nice utility to diff Jupyter Notebooks.
-#nbdime==1.0.5
+#nbdime==1.1.0
 
 # Optional: tqdm displays nice progress bars, ipywidgets for tqdm's notebook support
-tqdm==4.31.1
-ipywidgets==7.4.2
-
+tqdm==4.36.1
+ipywidgets==7.5.1