Python for Machine Learning
Python notebooks and experiments
Python Tutorial
python tutorial, staging for deep/machine learning course
1️⃣ Lesson 1 2️⃣ Lesson 2 3️⃣ Lesson 3 4️⃣ Lesson 4 5️⃣ lesson 5
Deep Learning
Originally designed to teach Alex python, thank you for your constant learning enthusiasm
Also created for coderbunker deep learning talk sessions
This course is the basic deep learning course that follows closely on Jeremy Howard’s fantasic /free /life-changing fast.ai course.
The most of notebooks are just trails we left behind passing on their awesomeness.
Checklist before we start and a reading list
Experiments
- Fast KMeans by batch with GPU, how to train a 60 minutes kmeans in 3 seconds, with example here
- A PyTorch training wrapper to simplify tracking
Environment Installation
Follow the installation instructions
Run the jupyter notebook on anaconda3 environment
Usual pre-requisites for the learning.
python 3.6
numpy == '1.14.3'
pandas == '0.23.0'
tensorflow == '1.8.0'
keras == '2.2.0'
Other versions of above library will probably work.
Assuming your anaconda3 is at ~/anaconda3/
If you don’t have any of these, try the following format in the command line:
~/anaconda3/bin/pip install keras==2.2.0
If you are on Mac:
~/anaconda3/bin/pip install torch torchvision
To install PyTorch. For other system, You’ll have to visit their homepage to copy/paste the right command to install.
Libs
In some lines of code you might see
from forgebox.imports import *
You can do
pip install forgebox
Contact Us
If you want to be a contributor:
mail: b2ray2c@gmail.com
wechat: 417848506 remark:”python4ml”