Thursday News: Stats, Math, ML, Neural Nets, K-means, AI, Deep Learning, Python, Anomaly Detection Source – datasciencecentral.com
Here is our selection of featured articles and technical resources posted since Monday:
- 29 Statistical Concepts Explained in Simple English – Part 1
- The Math Behind Machine Learning
- Use case of Machine Learning in Clean Energy Sector
- K-means: A step towards Marketing Mix Modeling
- Prediction at Scale with scikit-learn and PySpark Pandas
- AlexNet Implementation Using Keras
- Anomaly/Outlier Detection using Local Outlier Factors
- Question: Predictive Model Biasing the Target Variable?
- Critical Thinking and Becoming “Students of Data Science”
- The Case for Just Getting Your Feet Wet with AI
- Why is Becoming a Data Scientist so Difficult?
- Should Python Become Your Official Corporate Language – Along With English?
- Facial Recognition and its Applications
- A Research Data Scientist Explains ‘Deep Learning’
- A Data Scientist’s Guide to an Efficient Project Lifecycle
Enjoy the reading!