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https://github.com/noahgift/core-stats-datascience

Core Statistics for Datascience
https://github.com/noahgift/core-stats-datascience

core data-science pragmaticai statistics

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Core Statistics for Datascience

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# Core Statistics for datascience
Core Statistics for Datascience

## Outline for Talk

#### Part 1:

* [Introduction to Colab & Introduction to Data Science](https://paiml.github.io/python_for_datascience/intro.html)
* [Data science key facts](https://github.com/noahgift/core-stats-datascience/blob/master/Data_science_key_facts.ipynb)
* [Data science libraries](https://paiml.github.io/python_for_datascience/lessons/Lesson9_Python_For_Data_Science_Data_Science_Libraries.html)

#### Part 2:

Notebooks in this repo [EDA, Feature Engineering and Predictive Modeling Theory]:

* [Data Science Workflow](https://github.com/noahgift/core-stats-datascience/blob/master/data_science_workflow.ipynb)
* [Trends Supervised Learning](https://github.com/noahgift/core-stats-datascience/blob/master/Lesson2_7_Trends_Supervized_Learning.ipynb)
* [Clustering](https://github.com/noahgift/core-stats-datascience/blob/master/Lesson3_1_Cluster_Analysis.ipynb)
* [GMM](https://github.com/noahgift/core-stats-datascience/blob/master/Lesson3_2_GMM.ipynb)
* [PCA](https://github.com/noahgift/core-stats-datascience/blob/master/Lesson3_3_PCA.ipynb)
* [Recommendations](https://github.com/noahgift/core-stats-datascience/blob/master/Lesson3_5_recommendations.ipynb)
* [Network Analysis](https://github.com/noahgift/core-stats-datascience/blob/master/network_analysis.ipynb)

#### Part 3 (Bonus):

* Doing ML in the cloud: walk through census project AWS Sagemaker

### Additional Related Topics from Noah Gift

His most recent books are:

* [Pragmatic A.I.:   An introduction to Cloud-Based Machine Learning (Pearson, 2018)](https://www.amazon.com/Pragmatic-AI-Introduction-Cloud-Based-Analytics/dp/0134863860)
* [Python for DevOps (O'Reilly, 2020)](https://www.amazon.com/Python-DevOps-Ruthlessly-Effective-Automation/dp/149205769X). 

His most recent video courses are:

* [Essential Machine Learning and A.I. with Python and Jupyter Notebook LiveLessons (Pearson, 2018)](https://learning.oreilly.com/videos/essential-machine-learning/9780135261118)
* [AWS Certified Machine Learning-Specialty (ML-S) (Pearson, 2019)](https://learning.oreilly.com/videos/aws-certified-machine/9780135556597)
* [Python for Data Science Complete Video Course Video Training (Pearson, 2019)](https://learning.oreilly.com/videos/python-for-data/9780135687253)
* [AWS Certified Big Data - Specialty Complete Video Course and Practice Test Video Training (Pearson, 2019)](https://learning.oreilly.com/videos/aws-certified-big/9780135772324)
* [Building A.I. Applications on Google Cloud Platform (Pearson, 2019)](https://learning.oreilly.com/videos/building-ai-applications/9780135973462)
* [Pragmatic AI and Machine Learning Core Principles (Pearson, 2019)](https://learning.oreilly.com/videos/pragmatic-ai-and/9780136554714)
* [Data Engineering with Python and AWS Lambda (Pearson, 2019)](https://learning.oreilly.com/videos/data-engineering-with/9780135964330)

His most recent online courses are:

* [Microservices with this Udacity DevOps Nanodegree (Udacity, 2019)](https://www.udacity.com/course/cloud-dev-ops-nanodegree--nd9991)
* [Command Line Automation in Python (DataCamp, 2019)](https://www.datacamp.com/instructors/ndgift)
* [AWS Certified Cloud Practitioner 2020-Real World & Pragmatic](https://www.udemy.com/course/aws-certified-cloud-practitioner-2020-real-world-pragmatic/?referralCode=CAC679A7D08212773428).