Learn how to use keras for deep learning. keras uses either tensorflow or theano as backend. You can recognize digits from images and learn how to work with NumPy arrays and keras. ## Work with image processing You can learn the available packages for ima
- [Instructor] Deep learning is a hot new subject.…In space, deep learning uses artificial neural networks…which have been around for a while.…However, it uses some new ways of constructing the networks…and utilizes advances in hardware…to gain some very impressive results.…Google, for example,…is using deep learning in its speech-to-text system.…If you're curious, head over to Google and try it out.…Deep learning and artificial neural networks…are big subject and out of scope for this video…but I encourage you to explore the subject further.…There are many resources available online.…
There are several deep learning libraries available.…Lucky for us we can use most of them from Python.…We can choose from TensorFlow, Theano, Torch, and others.…We're going to use a library called Keras,…which is a bit more high-level…than other libraries mentioned.…Keras also lets you take a back-end.…You can either use TensorFlow or Theano…for doing the actual computation.…Google recently announced that tighter integration…between TensorFlow and Keras.…
- Working with Jupyter notebooks
- Using code cells
- Extensions to the Python language
- Markdown cells
- Editing notebooks
- NumPy basics
- Broadcasting, array operations, and ufuncs
- Folium and Geo
- Machine learning with scikit-learn
- Plotting with matplotlib and bokeh
- Branching into Numba, Cython, deep learning, and NLP
Skill Level Intermediate
1. Scientific Python Overview
2. The Jupyter Notebook
3. NumPy Basics
Manage environments5m 11s
6. Folium and Geo
7. NY Taxi Data
10. Other Packages
11. Development Process
Next steps1m 33s
- Mark as unwatched
- Mark all as unwatched
Are you sure you want to mark all the videos in this course as unwatched?
This will not affect your course history, your reports, or your certificates of completion for this course.Cancel
Take notes with your new membership!
Type in the entry box, then click Enter to save your note.
1:30Press on any video thumbnail to jump immediately to the timecode shown.
Notes are saved with you account but can also be exported as plain text, MS Word, PDF, Google Doc, or Evernote.