Update README URLs based on HTTP redirects

Author: ReadmeCritic

README.md

@@ -277,7 +277,7 @@ IPython Notebook(s) demonstrating various command lines for Linux, Git, etc.
 | [ruby](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/commands/misc.ipynb#ruby) | Used to interact with the AWS command line and for Jekyll, a blog framework that can be hosted on GitHub Pages. |
 | [jekyll](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/commands/misc.ipynb#jekyll) | Simple, blog-aware, static site generator for personal, project, or organization sites.  Renders Markdown or Textile and Liquid templates, and produces a complete, static website ready to be served by Apache HTTP Server, Nginx or another web server. |
 | [pelican](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/commands/misc.ipynb#pelican) | Python-based alternative to Jekyll. |
-| [django](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/commands/misc.ipynb#django) | High-level Python Web framework that encourages rapid development and clean, pragmatic design. It can be useful to share reports/analyses and for blogging. Lighter-weight alternatives include [Pyramid](https://github.com/Pylons/pyramid), [Flask](https://github.com/mitsuhiko/flask), [Tornado](https://github.com/tornadoweb/tornado), and [Bottle](https://github.com/bottlepy/bottle).
+| [django](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/commands/misc.ipynb#django) | High-level Python Web framework that encourages rapid development and clean, pragmatic design. It can be useful to share reports/analyses and for blogging. Lighter-weight alternatives include [Pyramid](https://github.com/Pylons/pyramid), [Flask](https://github.com/pallets/flask), [Tornado](https://github.com/tornadoweb/tornado), and [Bottle](https://github.com/bottlepy/bottle).
 
 ## misc
 
@@ -294,7 +294,7 @@ IPython Notebook(s) demonstrating miscellaneous functionality.
 
 Anaconda is a free distribution of the Python programming language for large-scale data processing, predictive analytics, and scientific computing that aims to simplify package management and deployment.
 
-Follow instructions to install [Anaconda](http://docs.continuum.io/anaconda/install.html) or the more lightweight [miniconda](http://conda.pydata.org/miniconda.html).
+Follow instructions to install [Anaconda](https://docs.continuum.io/anaconda/install) or the more lightweight [miniconda](http://conda.pydata.org/miniconda.html).
 
 ### pip-requirements
 
@@ -328,7 +328,7 @@ Notebooks tested with Python 2.7.x.
 * [TensorFlow Tutorials](https://github.com/pkmital/tensorflow_tutorials) by Parag K Mital
 * [Summer School 2015](https://github.com/mila-udem/summerschool2015) by mila-udem
 * [Kaggle](https://www.kaggle.com/)
-* [Yhat Blog](http://blog.yhathq.com/)
+* [Yhat Blog](http://blog.yhat.com/)
 
 ## contributing