/Machine_Learning

Tutorials/tips on machine learning related topics

Primary LanguageJupyter NotebookMIT LicenseMIT

Machine Learning

license MIT Python 3.6 Keras 2.2 tensorflow 1.8 spark 1.8 sagemaker 1.14.0

All codes related to software engineering, machine learning, artificial intelligence, and data science. I continuously update this repository to document my learnings for future references and to share the knowledge. Otherwise noted, I use Python3 on MacOS.

I make most frequent updates to the folders with * sign. Happy learning!

Directory

.
├── *Bash               # Everything related to bash/shell scripting
├── *Basics             # Python Basics 
├── *Classes            # Documentation of courses I take (more updates coming)
├── *Deep_Learning      # Everyhing Deep Learning, Tensorflow, Keras, etc 
├── *Machine_learning   # Everything Machine Learning
├── *NLP                # Anything Related to Natural Language Processing 
├── *RaspberryPi        # Useful knowledge and tools for using Raspberry Pi
├── *Research_Paper     # Documentation of research papers I read 
├── *Spark              # Everything Spark, PySpark, Distributed Computing

Go Watch

Here, I add interesting videos I've watched.

Never Stop Learning

Because field of machine learning is changing rapidly, it is important to keep up with new techniques and constantly learn. Good thing is that there is so much information online but it is easy to get lost. Here, I want to document some useful online resources or tips. I put mostly free resources.

I've been really enjoying a site called StatQuest recently. I find the videos to be perfect length and entertaining to watch. It explains so many statistical and machine learning concepts well. Check it out!

STATQUEST

Stay Up To Date:

Fundamentals

Intermediate

Advanced (or more in depth)

Textbooks / Reading

Interview

Optional

  • Udacity's AB Testing

Raspberry Pi Projects