Update to latest library versions

Author: ageron

01_the_machine_learning_landscape.ipynb

@@ -165,14 +165,6 @@
      "text": [
       "[[5.96242338]]\n"
      ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/ageron/miniconda3/envs/tf2/lib/python3.6/site-packages/sklearn/linear_model/base.py:485: RuntimeWarning: internal gelsd driver lwork query error, required iwork dimension not returned. This is likely the result of LAPACK bug 0038, fixed in LAPACK 3.2.2 (released July 21, 2010). Falling back to 'gelss' driver.\n",
-      "  linalg.lstsq(X, y)\n"
-     ]
     }
    ],
    "source": [

02_end_to_end_machine_learning_project.ipynb

@@ -2,71 +2,64 @@
 # on Windows or when using a GPU. Please see the installation
 # instructions in INSTALL.md
 
+
 ##### Core scientific packages
 jupyter==1.0.0
-matplotlib==3.1.3
-numpy==1.18.1
-pandas==1.0.3
-scipy==1.4.1
-
+matplotlib==3.3.2
+numpy==1.18.5
+pandas==1.1.3
+scipy==1.5.3
 
 ##### Machine Learning packages
-scikit-learn==0.22
+scikit-learn==0.23.2
 
 # Optional: the XGBoost library is only used in chapter 7
-xgboost==1.0.2
+xgboost==1.2.1
 
 # Optional: the transformers library is only using in chapter 16
-transformers==2.8.0
+transformers==3.3.1
 
 ##### TensorFlow-related packages
 
 # If you have a TF-compatible GPU and you want to enable GPU support, then
-# replace tensorflow with tensorflow-gpu, and replace tensorflow-serving-api
-# with tensorflow-serving-api-gpu.
+# replace tensorflow-serving-api with tensorflow-serving-api-gpu.
 # Your GPU must have CUDA Compute Capability 3.5 or higher support, and
 # you must install CUDA, cuDNN and more: see tensorflow.org for the detailed
 # installation instructions.
 
-tensorflow==2.1.0
-
+tensorflow==2.3.1
 # Optional: the TF Serving API library is just needed for chapter 19.
-tensorflow-serving-api==2.1.0
-#tensorflow-serving-api-gpu==2.1.0
+tensorflow-serving-api==2.3.0 # or tensorflow-serving-api-gpu if gpu
 
-tensorboard==2.1.1
-tensorboard-plugin-profile==2.2.0
-tensorflow-datasets==2.1.0
-tensorflow-hub==0.7.0
-tensorflow-probability==0.9.0
+tensorboard==2.3.0
+tensorboard-plugin-profile==2.3.0
+tensorflow-datasets==4.0.1
+tensorflow-hub==0.9.0
+tensorflow-probability==0.11.1
 
 # Optional: only used in chapter 13.
 # NOT AVAILABLE ON WINDOWS
-tfx==0.21.2
+tfx==0.24.1
 
 # Optional: only used in chapter 16.
 # NOT AVAILABLE ON WINDOWS
-tensorflow-addons==0.8.3
+tensorflow-addons==0.11.2
 
 ##### Reinforcement Learning library (chapter 18)
 
 # There are a few dependencies you need to install first, check out:
 # https://github.com/openai/gym#installing-everything
-gym[atari]==0.17.1
+gym[atari]==0.17.3
 # On Windows, install atari_py using:
 # pip install --no-index -f https://github.com/Kojoley/atari-py/releases atari_py
 
-tf-agents==0.3.0
-
+tf-agents==0.6.0
 
 ##### Image manipulation
-imageio==2.6.1
-Pillow==7.0.0
-scikit-image==0.16.2
-graphviz==0.13.2
-pydot==1.4.1
-opencv-python==4.2.0.32
-pyglet==1.5.0
+Pillow==8.0.0
+graphviz==0.14.2
+opencv-python==4.4.0.44
+pyglet==1.4.11
 
 #pyvirtualdisplay # needed in chapter 16, if on a headless server
                   # (i.e., without screen, e.g., Colab or VM)
@@ -78,24 +71,32 @@ pyglet==1.5.0
 joblib==0.14.1
 
 # Easy http requests
-requests==2.23.0
+requests==2.24.0
 
 # Nice utility to diff Jupyter Notebooks.
-nbdime==2.0.0
+nbdime==2.1.0
 
 # May be useful with Pandas for complex "where" clauses (e.g., Pandas
 # tutorial).
 numexpr==2.7.1
 
 # Optional: these libraries can be useful in the classification chapter,
 # exercise 4.
-nltk==3.4.5
-urlextract==0.14.0
+nltk==3.5
+urlextract==1.1.0
 
 # Optional: these libraries are only used in chapter 16
-spacy==2.2.4
-ftfy==5.7
+ftfy==5.8
 
 # Optional: tqdm displays nice progress bars, ipywidgets for tqdm's notebook support
-tqdm==4.43.0
+tqdm==4.50.2
 ipywidgets==7.5.1
+
+
+
+# Specific lib versions to avoid conflicts
+attrs==19.3.0
+cloudpickle==1.3.0
+dill==0.3.1.1
+gast==0.3.3
+httplib2==0.17.4