A Journey Into Deep Learning - I. Goal
As I am thinking of self-learning Machine Learning (ML), I want to quickly pick up the skills and foundation of Python. (I used more with R, Matlab during my PhD work). So, since last year when I was at 9-month pregnancy, I’ve completed Python for Data Science and ML Bootcamp, instructed by Jose Portilla. Today, I have some sorts of feeling that I know what I was doing as a mom (~ 6 months after giving birth). Then, I grab and read a book The Algebra of Happiness, make a coffee, and open my MacBook - thinking, I’d like to continue to learn more about ML as I have been always fascinated with data. In between my baby sleep-wake cycle, I read and code and write down what I did, even just a little bit.
On Saturday March 14, the world is fighting with coronavirus and my world is thrilling that I start the journey of learning new things, from this course Tensorflow 2 and Keras Deep Learning Bootcamp.
Hopefully, I can start making fun project soon through applying what I’ve learned every single time I have when my baby fall asleep and/or take a nap. Here I make notes of every steps and accomplishment, even just a little bit.
Don’t hate machine learning for being simple. Levers are simple too, but they can move the world. -Cassie Kozyrkov
TensorFlow Setup and Install
Here are the notes for myself:
- Downland Python 3.7 Version from Anaconda for MacOS
- Create a folder, named “TensorFlow” under Desktop/Gitproject/
- Downland the class materials into the created folder
What I should do next time for STARTING the course:
- Locate the path in terminal with this code
% cd Desktop/Gitproject/TensorFlow - Open terminal and type
% conda activate mytfenvfor setup TensorFlow Environment - Get into virtual env using
% jupyter notebook
