p.y.b:
Here is a list of what I believe are the 10 Practical Steps for #DataScience:

1. Programming
a. Python - https://lnkd.in/gGQ7cuv
b. R - https://lnkd.in/giMGbph
c. SQL - https://lnkd.in/gM8nMNP
d. Command Line - https://lnkd.in/e3EQuis

2. Stats/Prob/Math
a. Coursera's Statistics w/ R - https://lnkd.in/gGT9NEf
b. edX's Probability - https://lnkd.in/gpUyC3P
c. Khan Academy Linear Algebra - https://lnkd.in/gMshbX4

3. Data Viz
a. Python Matplotlib- https://lnkd.in/gr3ifNt
b. R ggplot2 - https://lnkd.in/eThJXNr

4. Data Manipulation
a. Python Pandas - https://lnkd.in/g9kfpX4
b. R dplyr - https://lnkd.in/gAWusih

5. #MachineLearning
a. Google Crash Course - https://lnkd.in/gSgkVcT
b. Stanford Coursera - https://lnkd.in/g8ZG557
c. ISLR Book - https://lnkd.in/gk8GPZC

6. Experimental Design
a. Udacity A/B Testing - https://lnkd.in/gCerh4f

7. Business Sense
a. Metrics - https://lnkd.in/gZAG7bS

8. Communication
a. Storytelling - https://lnkd.in/gwjxVUu

9. Profile Building
a. GitHub - https://lnkd.in/g4r9naJ
b. LinkedIn - https://lnkd.in/g-KHHEC
c. Kaggle - https://lnkd.in/gBC77Hu
d. DS Resume - https://lnkd.in/gU8WVAF

🏅 10. Job Search
a. Daily Expert Tips & Advice - https://lnkd.in/g8z-xXD
---
Hope this helps! 👍
Updated on my site - http://www.claoudml.co/

#Datascience #MachineLearning #Artificialintelligence #Statistics

#learning predictive analytics with python
#book
#Machine_learn

#deep learning adaptive computation
#book
@Machine_learn

#An Introduction to Neural
Networks and Deep Learning #Chapter1 @Machine_learn

#An Introduction to Deep
Convolutional Neural Nets for
Computer Vision #Chapter2 @Machine_learn

#Multi-Instance Multi-Stage
Deep Learning for Medical
Image Recognition
#Chapter4 @Machine_learn

#Automatic Interpretation of
Carotid Intima–Media
Thickness Videos Using
Convolutional Neural
Networks
#Chapter5 @Machine_learn

#Deep Cascaded Networks for
Sparsely Distributed Object
Detection from Medical
Images
#Chapter6 @Machine_learn

#Deep Voting and Structured
Regression for Microscopy
Image Analysis
#Chapter7 @Machine_learn

#Deep Learning Tissue
Segmentation in Cardiac
Histopathology Images #Chapter8 @Machine_learn

#Deformable MR Prostate
Segmentation via Deep
Feature Learning and Sparse
Patch Matching
#Chapter9 @Machine_learn

#Scalable High
Performance Image
Registration Framework
by Unsupervised Deep
Feature Representations
Learning
#Chapter11 @Machine_learn

#Chest Radiograph
Pathology Categorization
via Transfer Learning #Chapter13 @Machine_learn

#Nick_McClure_Tensorflow_machine
#book
@Machine_learn

#Basics_of_Linear_Algebra_for Machine Learning
#book
@Machine_learn

#An Encounter with Google's TensorFlow (Revised)
#tutorial
@Machine_learn

#logistic regression
#simple code
#spam detection
@Machine_learn
#author:@RaminMousa