1/ Chose a career as a Data Scientist, which benefits from intense focus. 2/ All the thoughts and tasks that i get in my head, if tasks are small, i try to do some of them immediately. Otherwise, i write it down, and keep a sticky which i close at the end of the day. 3/ Am 40, I have a partner, who has slowly realized that i am different, and since the past few years she coaches me to do tasks i dont like (submit expense reports). I happily give her pocket shopping money in exchange. 4/ I take notes at every meeting, Notion is my tool. 5/ Switching off, what's that? I realize my teams think that i am a maniac, and my wife thinks am too obsessed. I help my team do things, and tell them i can come across as too hot, and they need to let me to know to backoff. I like to watch movies, and do take a break from time to time.
HN user
abcininin
I have been using a consistent setup that hasn't yet failed me for the past 2 years.
1. Install Anaconda to your home user directory .
2. create environment using (conda create --name myenv python=3.6) .
3. Switch to the environment using (conda activate myenv) .
4. Use (conda install mypackage), (pip install mypackage) in that priority order .
5. Export environment using (conda env export > conda_env.yaml) .
6. Environment can be created on an other system using (conda env create -f conda_env.yaml) .
Anaconda: https://www.anaconda.com/distribution/#download-section .
Dockerized Anaconda: https://docs.anaconda.com/anaconda/user-guide/tasks/docker/ .
* Complete API review and lots of examples for Scikit-Learn
* Machine Learning Algorithms from scratch (Random Forest, Gradient Boosted Trees, OLS, multi-layer perceptron). Thanks Jason Brownlee
* Spark API and Spark ML Lib API familiarity
* Still plugging away through Stanford CS229 Aiming towards a job change in mid 2019. Hopefully it works out.
I wish there were concrete examples of how machine learning is being used.