# Content: References, Learning Guides, Etc. / Tutorial

Change Search Criteria:### iPython Notebooks

Cheat Sheets / References, Learning Guides, Etc. / TutorialFrom GitHub: “This repo contains various iPython notebooks I’ve created to experiment with libraries and work through exercises, and explore subjects that I find interesting.” The notebooks include: Popular Python data science libraries NumPy SciPy Matplotlib Pandas Statsmodels Scikit-learn Seaborn NetworkX PyMC NLTK DEAP Genism Machine Learning Exercises Tensorflow Deep Learning Exercises Spark Big Data Labs Miscellaneous

### Learn Data Science

Curricula / Intro Guide / References, Learning Guides, Etc. / TutorialFrom GitHub: “A collection of Data Science Learning materials in the form of iPython Notebooks. Associated data sets. The initial beta release consists of four major topics Linear Regression Logistic Regression Random Forests K-Means Clustering Each of the above has at least three iPython Notebooks covering Overview (an exposition of the technique for the math-wary) Data Exploration (the nuts and bolts of real world data wrangling) Analysis (using the technique to … Continue Reading

### An Example Machine Learning Notebook

References, Learning Guides, Etc. / TutorialFrom GitHub: “In this notebook, I’m going to go over a basic Python data analysis pipeline from start to finish to show you what a typical data science workflow looks like. In addition to providing code examples, I also hope to imbue in you a sense of good practices so you can be a more effective — and more collaborative — data scientist. I will be following along with the … Continue Reading

### Multiple Hypothesis Testing

References, Learning Guides, Etc. / TutorialFrom MultiThreaded: “In recent years, there has been a lot of attention on hypothesis testing and so-called ‘p-hacking’, or misusing statistical methods to obtain more ‘significant’ results…. This post introduces some of the interesting phenomena that can occur when we are dealing with testing hypotheses. First, we consider an example of a single hypothesis test which gives great insight into the difference between significance and “being correct”. Next, we look … Continue Reading

### Perfect way to build a Predictive Model in less than 10 minutes

References, Learning Guides, Etc. / TutorialFrom Analytics Vidhya: ” have created modules on Python and R which can takes in tabular data and the name of target variable and BOOM! I have my first model in less than 10 minutes (Assuming your data has more than 100,000 observations). For smaller data sets, this can be even faster. The reason of submitting this super-fast solution is to create a benchmark for yourself on which you need to improve. … Continue Reading

### Build a Predictive Model in 10 Minutes (using Python)

References, Learning Guides, Etc. / TutorialFrom Analytics Vidhya: “Last week, we published “Perfect way to build a Predictive Model in less than 10 minutes using R“. Any one can guess a quick follow up to this article. Given the rise of Python in last few years and its simplicity, it makes sense to have this tool kit ready for the Pythonists in the data science world. I will follow similar structure as previous article with my additional … Continue Reading

### Essentials of Machine Learning Algorithms (with Python and R Codes)

Cheat Sheets / References, Learning Guides, Etc. / TutorialFrom Analytics Vidhya: “Today, as a data scientist, I can build data crunching machines with complex algorithms for a few dollors per hour. But, reaching here wasn’t easy! I had my dark days and nights…. The idea behind creating this guide is to simplify the journey of aspiring data scientists and machine learning enthusiasts across the world. Through this guide, I will enable you to work on machine learning problems and … Continue Reading

### Introduction to TensorFlow

References, Learning Guides, Etc. / TutorialThis tutorial is a series of slides introducing TensorFlow for artificial intelligence and machine learning, and covering the following topics: Motivation and abstract model Gentle introduction: NN feedforward Not-as-gentle: learning with SGD Sequence-to-sequence learning

### Bivariate Linear Regression

References, Learning Guides, Etc. / Tutorialfrom datascience+: “Regression is one of the – maybe even the single most important fundamental tool for statistical analysis in quite a large number of research areas. It forms the basis of many of the fancy statistical methods currently en vogue in the special sciences. Multilevel analysis and structural equation modeling are perhaps the most widespread and most obvious extensions of regression analysis that are applied in a large chunk of current … Continue Reading

### Bayesian Modelling in Python

References, Learning Guides, Etc. / Tutorial“Welcome to ‘Bayesian Modelling in Python’ – a tutorial for those interested in learning how to apply bayesian modelling techniques in python (PYMC3). This tutorial doesn’t aim to be a bayesian statistics tutorial – but rather a programming cookbook for those who understand the fundamental of bayesian statistics and want to learn how to build bayesian models using python. The tutorial sections and topics can be seen below. Contents Introduction Motivation … Continue Reading

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