- Data Science Bootcamp in Zurich, Switzerland, January 15 – April 6, 2018 - Oct 12, 2017.
Come to the land of chocolate and Data Science where the local tech scene is booming and the jobs are a plenty. Learn the most important concepts from top instructors by doing and through projects. Use code KDNUGGETS to save.
Tags: Bootcamp, Data Science, Data Visualization, Machine Learning, NLP, Python, R, Switzerland, Zurich
- Best practices of orchestrating Python and R code in ML projects - Oct 12, 2017.
Instead of arguing about Python vs R I will examine the best practices of integrating both languages in one data science project.
Pages: 1 2
Tags: DVC, Machine Learning, Python, Python vs R, R
- How I started with learning AI in the last 2 months - Oct 9, 2017.
The relevance of a full stack developer will not be enough in the changing scenario of things. In the next two years, full stack will not be full stack without AI skills.
Tags: AI, Chatbots, Gradient Descent, Neural Networks, Python
- Neural Networks: Innumerable Architectures, One Fundamental Idea - Oct 4, 2017.
At the end of this post, you’ll be able to implement a neural network to identify handwritten digits using the MNIST dataset and have a rough time idea about how to build your own neural networks.
Pages: 1 2
Tags: AI, Machine Learning, Neural Networks, Python, TensorFlow
Top 10 Videos on Machine Learning in Finance - Sep 29, 2017.
Talks, tutorials and playlists – you could not get a more gentle introduction to Machine Learning (ML) in Finance. Got a quick 4 minutes or ready to study for hours on end? These videos cover all skill levels and time constraints!
Tags: Credit Risk, Finance, Investment Portfolio, Machine Learning, Python, R, Stocks, Tutorials, Videolectures, Youtube
- Tensorflow Tutorial, Part 2 – Getting Started - Sep 28, 2017.
This tutorial will lay a solid foundation to your understanding of Tensorflow, the leading Deep Learning platform. The second part shows how to get started, install, and build a small test case.
Tags: Deep Learning, GPU, Python, TensorFlow
- Keras Cheat Sheet: Deep Learning in Python - Sep 27, 2017.
Keras is a Python deep learning library for Theano and TensorFlow. The package is easy to use and powerful, as it provides users with a high-level neural networks API to develop and evaluate deep learning models. With this library, you’ll be making neural network models in no time!
Pages: 1 2
Tags: Cheat Sheet, DataCamp, Deep Learning, Keras, Neural Networks, Python
- Spark – The Definitive Guide – exclusive preview - Sep 25, 2017.
Get an exclusive preview of "Spark: The Definitive Guide" from Databricks! Learn how Spark runs on a cluster, see examples in SQL, Python and Scala, Learn about Structured Streaming and Machine Learning and more.
Tags: Apache Spark, Databricks, Free ebook, Python, Scala, SQL
- Python Data Preparation Case Files: Group-based Imputation - Sep 25, 2017.
The second part in this series addresses group-based imputation for dealing with missing data values. Check out why finding group means can be a more formidable action than overall means, and see how to accomplish it in Python.
Tags: Data Preparation, Pandas, Python
- The Easy Button for R & Python on Spark, Webinar Oct 18 - Sep 22, 2017.
Learn five solid reasons to use managed services for Cloudera for R, Python and other advanced analytics on Spark & Hadoop in the cloud.
Tags: Apache Spark, Cazena, Cloud Analytics, Cloudera, Python, R
- Putting Machine Learning in Production - Sep 22, 2017.
In machine learning, going from research to production environment requires a well designed architecture. This blog shows how to transfer a trained model to a prediction server.
Tags: Data Science, Data Science Platform, Machine Learning, Production, Python, Skills
30 Essential Data Science, Machine Learning & Deep Learning Cheat Sheets - Sep 22, 2017.
This collection of data science cheat sheets is not a cheat sheet dump, but a curated list of reference materials spanning a number of disciplines and tools.
Pages: 1 2 3
Tags: Cheat Sheet, Data Science, Deep Learning, Machine Learning, Neural Networks, Probability, Python, R, SQL, Statistics
- Top KDnuggets tweets, Sep 13-19: Top Books on NLP; What Else Can AI Guess From Your Face? - Sep 20, 2017.
Also: The Ten Fallacies of Data Science; #Python #Pandas tips and tricks; Geoff Hinton says we need to start all over.
Tags: Geoff Hinton, NLP, Pandas, Python, Top tweets
- 5 Machine Learning Projects You Can No Longer Overlook – Episode VI - Sep 20, 2017.
Deep learning, data preparation, data visualization, oh my! Check out the latest installation of '5 Machine Learning Projects You Can No Longer Overlook' for insight on... well, what machine learning projects you can no longer overlook.
Tags: Data Visualization, Datasets, Deep Learning, Javascript, Machine Learning, Netflix, Overlook, Python, Spark
- Keras Tutorial: Recognizing Tic-Tac-Toe Winners with Neural Networks - Sep 18, 2017.
In this tutorial, we will build a neural network with Keras to determine whether or not tic-tac-toe games have been won by player X for given endgame board configurations. Introductory neural network concerns are covered.
Tags: Games, Keras, Neural Networks, Python
- Best Data Science, Machine Learning Courses from Udemy (only $12 until Sep 20) - Sep 14, 2017.
Back-to-school sale on best courses from Udemy, including Data Science, Machine Learning, Python, Spark, Tableau, and Hadoop - only $12 until Sep 20, 2017.
Tags: Apache Spark, Hadoop, Machine Learning, Online Education, Python, Tableau, Udemy
- Python Data Preparation Case Files: Removing Instances & Basic Imputation - Sep 14, 2017.
This is the first of 3 posts to cover imputing missing values in Python using Pandas. The slowest-moving of the series (out of necessity), this first installment lays out the task and data at the risk of boring you. The next 2 posts cover group- and regression-based imputation.
Tags: Data Preparation, Pandas, Python
- Top KDnuggets tweets, Sep 06-12: Visualizing Cross-validation Code; Intro to #Blockchain and #BigData - Sep 13, 2017.
Also: WTF #Python - A collection of interesting and tricky Python examples; Thoughts after taking @AndrewYNg #Deeplearning #ai course; Another #Keras Tutorial For #NeuralNetwork Beginners.
Tags: Andrew Ng, Blockchain, Cross-validation, Jeremy Howard, Keras, Python, Top tweets
- KDnuggets™ News 17:n35, Sep 13: Putting the “Science” Back in Data Science; Python vs. R: And the leader is… - Sep 13, 2017.
Putting the "Science" Back in Data Science; Python vs R - Who Is Really Ahead in Data Science, Machine Learning; I built a chatbot in 2 hours and this is what I learned; Are Data Lakes Fake News?; Python Overtaking R?
Tags: Chatbot, Data Lakes, Data Science, Machine Learning, Python, R, Use Cases
Python vs R – Who Is Really Ahead in Data Science, Machine Learning? - Sep 12, 2017.
We examine Google Trends, job trends, and more and note that while Python has only a small advantage among current Data Science and Machine Learning related jobs, this advantage is likely to increase in the future.
Tags: Data Science, Google Trends, Jobs, Kaggle, Machine Learning, Python, Python vs R, R
- Python vs R for Artificial Intelligence, Machine Learning, and Data Science - Sep 11, 2017.
This is a summary (with links) of a three-part article series that's intended to be an in-depth overview of the considerations, tradeoffs, and recommendations associated with selecting between Python and R for programmatic data science tasks.
Tags: AI, Data Science, Machine Learning, Python, Python vs R, R
- Accelerating Your Algorithms in Production with Python and Intel MKL, Sep 21 - Sep 8, 2017.
We will provide tips for data scientists to speed up Python algorithms, including a discussion on algorithm choice, and how effective package tool can make large differences in performance.
Tags: ActiveState, Intel, Production, Python
- Python Overtaking R? - Sep 8, 2017.
Did Python overtake R? We examine and compare 3 different blogs that deal with this question.
Tags: Burtch Works, Python, Python vs R, R
- Top KDnuggets tweets, Aug 30 – Sep 5: Python overtakes R, becomes the leader in #DataScience; Humble Book Bundle: #DataScience - Sep 6, 2017.
Also: Pandas tips and tricks #Python #DataScience; How I replicated an $86 million project in 57 lines of code; Future #MachineLearning Class.
Tags: Machine Learning, Pandas, Python, Top tweets
- New books on Data Science and Machine Learning from Chapman & Hall/CRC Press – Save 20% - Sep 5, 2017.
New books on Data Science and Analytics with Python, Large-Scale Machine Learning in the Earth Sciences, and Social Networks with Rich Edge Semantics - save 20% with code JWR38.
Tags: Books, CRC Press, Data Science, Python, Social Networks
- Visualizing Cross-validation Code - Sep 5, 2017.
Cross-validation helps to improve your prediction using the K-Fold strategy. What is K-Fold you asked? Check out this post for a visualized explanation.
Tags: Cross-validation, Machine Learning, Python, scikit-learn
- Search Millions of Documents for Thousands of Keywords in a Flash - Sep 1, 2017.
We present a python library called FlashText that can search or replace keywords / synonyms in documents in O(n) – linear time.
Tags: Algorithms, Data Science, GitHub, NLP, Python, Search Engine, Text Mining
- KDnuggets™ News 17:n33, Aug 30: Python Overtakes R in Machine Learning; Data Science in 42 Steps; Deep Learning not AI’s Future - Aug 30, 2017.
Also: KDnuggets part-time, paid internship in Data Science/Machine Learning Journalism; How To Write Better SQL Queries: The Definitive Guide; Understanding overfitting: an inaccurate meme in Machine Learning; How to Become a Data Scientist: The Definitive Guide
Tags: AI, Data Science, Deep Learning, Machine Learning, Poll, Python, R
Data Scientists: What They Do and How to Become One - Aug 29, 2017.
Data science is growing, and will continue to grow for the foreseeable future. Whether you are a student or an expert, here are courses to help further your knowledge of this promising field.
Tags: Data Science, Data Science Education, edX, Microsoft, Programming, Python, UCSD
Python overtakes R, becomes the leader in Data Science, Machine Learning platforms - Aug 28, 2017.
While Python did not "swallow" R, in 2017 Python ecosystem overtook R as the leading platform for Analytics, Data Science, and Machine Learning and is pulling users from other platforms.
Tags: Data Science Platform, Poll, Python, Python vs R, R
42 Steps to Mastering Data Science - Aug 25, 2017.
This post is a collection of 6 separate posts of 7 steps a piece, each for mastering and better understanding a particular data science topic, with topics ranging from data preparation, to machine learning, to SQL databases, to NoSQL and beyond.
Tags: Data Preparation, Data Science, Deep Learning, Machine Learning, NoSQL, Python, SQL
- KDnuggets™ News 17:n32, Aug 23: The Rise of GPU Databases; Instagramming with Python for Data Analysis - Aug 23, 2017.
Also: Deep Learning and Neural Networks Primer; A New Beginning to Deep Learning; The most important step in Machine Learning process.
Tags: Databases, GPU, Instagram, Python
- A Guide to Instagramming with Python for Data Analysis - Aug 17, 2017.
I am writing this article to show you the basics of using Instagram in a programmatic way. You can benefit from this if you want to use it in a data analysis, computer vision, or any other cool project you can think of.
Pages: 1 2
Tags: Data Analysis, Image Recognition, Instagram, Python
- Top KDnuggets tweets, Aug 09-15: #Tensorflow tutorials and best practices; Top Influencers for #DataScience - Aug 16, 2017.
Also 37 Reasons why your #NeuralNetwork is not working; Making Predictive Model Robust: Holdout vs Cross-Validation.
Tags: Influencers, Python, TensorFlow, Top tweets
- New Poll: Python vs R vs rest: What did you use in 2016-17 for Analytics, Data Science, Machine Learning tasks? - Aug 15, 2017.
Python vs R vs Other - What did you use for Analytics, Data Science, Machine Learning work in 2016-17? Vote and we will analyze and report results and trends.
Tags: Data Science Platform, Poll, Python, Python vs R, R
- Comparing Distance Measurements with Python and SciPy - Aug 15, 2017.
This post introduces five perfectly valid ways of measuring distances between data points. We will also perform simple demonstration and comparison with Python and the SciPy library.
Tags: Clustering, K-means, Python, SciPy
- Best Data Science, Machine Learning Courses from Udemy (only $10 or $12 till Aug 10) - Aug 6, 2017.
Back-to-school sale on best courses from Udemy, including Data Science, Machine Learning, Python, Spark, Tableau, and Hadoop - only $10 or $12 until Aug 10, 2017.
Tags: Apache Spark, Hadoop, Machine Learning, Online Education, Python, Tableau, Udemy
- Top KDnuggets tweets, Jul 26 – Aug 01: 37 Reasons why your #NeuralNetwork is not working; Machine Learning Exercises in Python - Aug 2, 2017.
Also Hill criteria for #causality vs #correlation via #xkcd cartoons; #MachineLearning Workflows in #Python from Scratch Part 2: k-means Clustering
Tags: Causation, Machine Learning, Neural Networks, Python, TensorFlow, Top tweets
- KDnuggets™ News 17:n29, Aug 2: Machine Learning Exercises in Python; 8 Reasons Why Many Big Data Analytics Solutions Fail - Aug 2, 2017.
Machine Learning Exercises in Python: An Introductory Tutorial Series; The BI & Data Analysis Conundrum: 8 Reasons Why Many Big Data Analytics Solutions Fail to Deliver Value; The Internet of Things: An Introductory Tutorial Series; How to squeeze the most from your training data
Tags: Analytics, Big Data, Classification, Convolutional Neural Networks, Data Visualization, IoT, Machine Learning, Python
Machine Learning Exercises in Python: An Introductory Tutorial Series - Jul 26, 2017.
This post presents a summary of a series of tutorials covering the exercises from Andrew Ng's machine learning class on Coursera. Instead of implementing the exercises in Octave, the author has opted to do so in Python, and provide commentary along the way.
Tags: Andrew Ng, Machine Learning, Python
6 Reasons Why Python Is Suddenly Super Popular - Jul 25, 2017.
Python is a general-purpose language — sometimes referred to as utilitarian — which is designed to be simple to read and write. The point that it’s not a complex language is important.
Tags: Programming Languages, Python
- Revolutionizing Data Science Package Management, July 25 - Jul 24, 2017.
Learn how Anaconda solves one of the most headache-inducing problems in data science—overcoming the package dependency nightmare—through the power of conda, in this webinar, on July 25.
Tags: Anaconda, Continuum Analytics, Data Science, Python
- Road Lane Line Detection using Computer Vision models - Jul 19, 2017.
A tutorial on how to implement a computer vision data pipeline for road lane detection used by self-driving cars.
Pages: 1 2
Tags: AI, Computer Vision, Data Science, Machine Learning, Python, Self-Driving Car
- JupyterCon – Collaborative Data Science, New York, August 22-25 - Jul 10, 2017.
Bloomberg, Microsoft, Netflix and others found how Jupyter Notebook - the new front end for collaborative data science - make data a competitive advantage. Save an extra 20% with code PCKDNG.
Tags: Collaborative, Data Science, Jupyter, New York City, NY, O'Reilly, Python
- Exploratory Data Analysis in Python - Jul 7, 2017.
We view EDA very much like a tree: there is a basic series of steps you perform every time you perform EDA (the main trunk of the tree) but at each step, observations will lead you down other avenues (branches) of exploration by raising questions you want to answer or hypotheses you want to test.
Tags: Data Analysis, Data Exploration, Data Preparation, Jupyter, Python, SVDS
- Getting Started with Python for Data Analysis - Jul 5, 2017.
A guide for beginners to Python for getting started with data analysis.
Tags: Beginners, Data Analysis, Jupyter, numpy, Python
- Text Clustering : Quick insights from Unstructured Data, part 2 - Jul 4, 2017.
We will build this in a modular way and also focus on exposing the functionalities as an API so that it can serve as a plug and play model without any disruptions to the existing systems.
Tags: API, Clustering, Python, Text Analytics, Unstructured data
- How Feature Engineering Can Help You Do Well in a Kaggle Competition – Part 3 - Jul 4, 2017.
In this last post of the series, I describe how I used more powerful machine learning algorithms for the click prediction problem as well as the ensembling techniques that took me up to the 19th position on the leaderboard (top 2%)
Tags: Feature Engineering, Jupyter, Kaggle, Machine Learning, Python
- How Feature Engineering Can Help You Do Well in a Kaggle Competition – Part 2 - Jun 27, 2017.
In this post, I describe the competition evaluation, the design of my cross-validation strategy and my baseline models using statistics and trees ensembles.
Pages: 1 2
Tags: Feature Engineering, Jupyter, Kaggle, Machine Learning, Python
Emerging Ecosystem: Data Science and Machine Learning Software, Analyzed - Jun 21, 2017.
We examine which top tools are "friends", their Python vs R bias, and which work well with Spark/Hadoop and Deep Learning, and identify an emerging Big Data Deep Learning ecosystem.
Pages: 1 2
Tags: Big Data, Data Mining Software, Deep Learning, Poll, Python, Python vs R
- Best Data Science Courses from Udemy (only $10 till June 21) - Jun 19, 2017.
Here are some of the best courses in data science from Udemy, covering Data Science, Machine Learning, Python, Spark, Tableau, and Hadoop - only $10 until June 21, 2017.
Tags: Apache Spark, Hadoop, Machine Learning, Online Education, Python, Tableau, Udemy
- KDnuggets™ News 17:n23, Jun 14: The Practice of Machine Learning, Data Science Implementation, and Feature Selection - Jun 14, 2017.
A Practical Guide to Machine Learning; Your Checklist to Get Data Science Implemented in Production; The Practical Importance of Feature Selection; Machine Learning in Real Life: Tales from the Trenches.
Tags: Feature Selection, Machine Learning, Production, Python
Top 15 Python Libraries for Data Science in 2017 - Jun 13, 2017.
Since all of the libraries are open sourced, we have added commits, contributors count and other metrics from Github, which could be served as a proxy metrics for library popularity.
Pages: 1 2
Tags: Data Mining, Data Science, Deep Learning, Machine Learning, Natural Language Processing, Python, Visualization
- How Feature Engineering Can Help You Do Well in a Kaggle Competition – Part I - Jun 8, 2017.
As I scroll through the leaderboard page, I found my name in the 19th position, which was the top 2% from nearly 1,000 competitors. Not bad for the first Kaggle competition I had decided to put a real effort in!
Tags: Apache Spark, Feature Engineering, Jupyter, Kaggle, Machine Learning, Python
- Machine Learning Workflows in Python from Scratch Part 2: k-means Clustering - Jun 7, 2017.
The second post in this series of tutorials for implementing machine learning workflows in Python from scratch covers implementing the k-means clustering algorithm.
Tags: Clustering, K-means, Machine Learning, Python, Workflow
- KDnuggets™ News 17:n22, Jun 7: 7 Steps to Mastering Data Preparation with Python; Why Does Deep Learning Not Have a Local Minimum? - Jun 7, 2017.
7 Steps to Mastering Data Preparation with Python; Why Does Deep Learning Not Have a Local Minimum?; 7 Techniques to Handle Imbalanced Data; Which Machine Learning Algorithm Should I Use?; Is Regression Analysis Really Machine Learning?
Tags: Data Preparation, Deep Learning, Machine Learning, Python, Regression, Unbalanced
- 6 Interesting Things You Can Do with Python on Facebook Data - Jun 6, 2017.
Facebook has a huge amount of data that is available for you to explore, you can do many things with this data. I will be sharing my experience with you on how you can use the Facebook Graph API for analysis with Python.
Tags: Facebook, Pandas, Python
- 7 Steps to Mastering Data Preparation with Python - Jun 2, 2017.
Follow these 7 steps for mastering data preparation, covering the concepts, the individual tasks, as well as different approaches to tackling the entire process from within the Python ecosystem.
Pages: 1 2
Tags: 7 Steps, Data Preparation, Data Preprocessing, Data Science, Data Wrangling, Machine Learning, Pandas, Python
- Data Science for Newbies: An Introductory Tutorial Series for Software Engineers - May 31, 2017.
This post summarizes and links to the individual tutorials which make up this introductory look at data science for newbies, mainly focusing on the tools, with a practical bent, written by a software engineer from the perspective of a software engineering approach.
Tags: Apache Spark, Data Science, Jupyter, Machine Learning, Pandas, Python, Reddit, Scala, SQL
- KDnuggets™ News 17:n21, May 31: Python Machine Learning Workflows from Scratch; Machine Learning Crash Course - May 31, 2017.
Machine Learning Workflows in Python from Scratch Part 1: Data Preparation; Machine Learning Crash Course: Part 1; An Introduction to the MXNet Python API; How A Data Scientist Can Improve Productivity; Data science platforms are on the rise and IBM is leading the way
Tags: Data Preparation, Data Science, Data Science Platform, Data Scientist, Machine Learning, Python
- Data preprocessing for deep learning with nuts-ml - May 30, 2017.
Nuts-ml is a new data pre-processing library in Python for GPU-based deep learning in vision. It provides common pre-processing functions as independent, reusable units. These so called ‘nuts’ can be freely arranged to build data flows that are efficient, easy to read and modify.
Tags: Data Preparation, Deep Learning, IBM, Image Recognition, Python
Machine Learning Workflows in Python from Scratch Part 1: Data Preparation - May 29, 2017.
This post is the first in a series of tutorials for implementing machine learning workflows in Python from scratch, covering the coding of algorithms and related tools from the ground up. The end result will be a handcrafted ML toolkit. This post starts things off with data preparation.
Tags: Data Preparation, Machine Learning, Python, Workflow
- An Introduction to the MXNet Python API - May 26, 2017.
This post outlines an entire 6-part tutorial series on the MXNet deep learning library and its Python API. In-depth and descriptive, this is a great guide for anyone looking to start leveraging this powerful neural network library.
Tags: API, AWS, Deep Learning, Neural Networks, Python
- DataScience.com Releases Python Package for Interpreting the Decision-Making Processes of Predictive Models - May 24, 2017.
DataScience.com new Python library, Skater, uses a combination of model interpretation algorithms to identify how models leverage data to make predictions.
Tags: Datascience.com, GitHub, Interpretability, Python
New Leader, Trends, and Surprises in Analytics, Data Science, Machine Learning Software Poll - May 22, 2017.
Python caught up with R and (barely) overtook it; Deep Learning usage surges to 32%; RapidMiner remains top general Data Science platform; Five languages of Data Science.
Pages: 1 2
Tags: Anaconda, Data Mining Software, Poll, Python, R, RapidMiner, Spark, TensorFlow
- The Path To Learning Artificial Intelligence - May 19, 2017.
Learn how to easily build real-world AI for booming tech, business, pioneering careers and game-level fun.
Tags: AI, Artificial Intelligence, Deep Learning, Machine Learning, Online Education, Python
- Simplifying Decision Tree Interpretability with Python & Scikit-learn - May 19, 2017.
This post will look at a few different ways of attempting to simplify decision tree representation and, ultimately, interpretability. All code is in Python, with Scikit-learn being used for the decision tree modeling.
Tags: Decision Trees, Interpretability, Python, scikit-learn
The Best Python Packages for Data Science - May 19, 2017.
This report is the second in a series analyzing data science related topics. This time around, specifically, we rank 15 top Python data science packages, hopefully with results of use to the data science community.
Tags: Data Incubator, Data Science, Python
- Best Data Science Courses from Udemy (only $10 till May 27) - May 17, 2017.
Here a list of the best courses in data science from Udemy, covering Data Science, Machine Learning, Python, Spark, Tableau, and Hadoop - only $10 until May 27, 2017.
Tags: Apache Spark, Hadoop, Machine Learning, Online Education, Python, Tableau, Udemy
- Join 1 Million Others on DataCamp (50% off until May 23) - May 16, 2017.
DataCamp is celebrating 1 millions learners on its platform and is offering 50% off for unlimited access until May 23. Learn R and Python for data science interactively at your own pace.
Tags: Data Science Education, Data Visualization, DataCamp, Online Education, Python, R
- Deep Learning in Minutes with this Pre-configured Python VM Image - May 5, 2017.
Check out this Python deep learning virtual machine image, built on top of Ubuntu, which includes a number of machine learning tools and libraries, along with several projects to get up and running with right away.
Tags: Deep Learning, Machine Learning, Python
- Top KDnuggets tweets, Apr 26 – May 02: Face Recognition with Python, in under 25 lines of code - May 3, 2017.
Face Recognition with Python, in under 25 lines of code; Try #DeepLearning in #Python w. a fully pre-configured VM; Homo Bayesians #MachineLearning #humor #cartoon; The Most Popular Language For #MachineLearning, #DataScience Is ...
Tags: Deep Learning, Face Recognition, Pandas, Python, Top tweets
- KDnuggets™ News 17:n17, May 3: Learn Machine Learning… in 10 Days?!? Gradient Descent, Simplified - May 3, 2017.
How to Learn Machine Learning in 10 Days; Keep it simple! How to understand Gradient Descent algorithm; The Guerrilla Guide to Machine Learning with Python; What Data You Analyzed - KDnuggets Poll Results and Trends; Cartoon: Machine Learning - What They Think I Do
Tags: Cartoon, Gradient Descent, Machine Learning, Neural Networks, Poll, Python, TensorFlow
- How Not To Program the TensorFlow Graph - May 1, 2017.
Using TensorFlow from Python is like using Python to program another computer. Being thoughtful about the graphs you construct can help you avoid confusion and costly performance problems.
Tags: Deep Learning, Programming, Python, TensorFlow
- The Guerrilla Guide to Machine Learning with Python - May 1, 2017.
Here is a bare bones take on learning machine learning with Python, a complete course for the quick study hacker with no time (or patience) to spare.
Tags: Deep Learning, Machine Learning, Pandas, Python, scikit-learn, Sebastian Raschka
- Dask and Pandas and XGBoost: Playing nicely between distributed systems - Apr 27, 2017.
This blogpost gives a quick example using Dask.dataframe to do distributed Pandas data wrangling, then using a new dask-xgboost package to setup an XGBoost cluster inside the Dask cluster and perform the handoff.
Tags: Dask, Distributed Systems, Pandas, Python, XGBoost
- Best Data Science Courses from Udemy (only $10 till Apr 29) - Apr 24, 2017.
Here a list of the best courses in data science from Udemy, covering Data Science, Machine Learning, Python, Spark, Tableau, and Hadoop - only $10 until April 29, 2017.
Tags: Apache Spark, Hadoop, Machine Learning, Online Education, Python, Tableau, Udemy
- Data Science Dividends – A Gentle Introduction to Financial Data Analysis - Apr 24, 2017.
This post outlines some very basic methods for performing financial data analysis using Python, Pandas, and Matplotlib, focusing mainly on stock price data. A good place for beginners to start.
Pages: 1 2
Tags: Finance, Pandas, Python
- Top KDnuggets tweets, Apr 12-18: 10 Free Must-Read Books for #MachineLearning and #DataScience - Apr 19, 2017.
Also Modern NLP in Python, or What you can learn about food by analyzing a million Yelp reviews; The Periodic Table of #DataScience; What is #Blockchain Technology?
Tags: Blockchain, Data Science, Free ebook, NLP, Python, Top tweets, Yelp
New Online Data Science Tracks for 2017 - Apr 17, 2017.
In 2017 there are many new and revamped data science tracks that are much more comprehensive for beginners than ever before. The tracks are designed to give you the skills you need to grab a job in data science, and some even have a job guarantee.
Pages: 1 2
Tags: Coursera, DataCamp, edX, Online Education, Python, R, Springboard
- 5 Machine Learning Projects You Can No Longer Overlook, April - Apr 13, 2017.
It's about that time again... 5 more machine learning or machine learning-related projects you may not yet have heard of, but may want to consider checking out. Find tools for data exploration, topic modeling, high-level APIs, and feature selection herein.
Tags: Data Exploration, Deep Learning, Java, Machine Learning, Neural Networks, Overlook, Python, Scala, scikit-learn, Topic Modeling
- Top KDnuggets tweets, Apr 05-11: 10 Free Must-Read Books for Machine Learning, Data Science; Making beautiful data visualizations in Python, matplotlib - Apr 12, 2017.
10 Free Must-Read Books for Machine Learning and Data Science; How to make beautiful data visualizations in Python with matplotlib; #DeepLearning in 7 lines of code; Data Science of Variable Selection: A Review.
Tags: Data Visualization, Free ebook, Matplotlib, Python, Top tweets
- Introduction to Anomaly Detection - Apr 3, 2017.
This overview will cover several methods of detecting anomalies, as well as how to build a detector in Python using simple moving average (SMA) or low-pass filter.
Tags: Anomaly Detection, Datascience.com, Python, Time Series
- A Short Guide to Navigating the Jupyter Ecosystem - Mar 31, 2017.
This post presents a no-nonsense overview of the Jupyter ecosystem, and a few tips, tricks and concepts you may find useful for navigating it.
Tags: Jupyter, Python, SVDS
- Top KDnuggets tweets, Mar 22-28: Big #DataScience: Expectation vs. Reality - Mar 29, 2017.
Also A Gentle Introduction To Graph Theory; An Overview of #Python #DeepLearning Frameworks; The Great Algorithm Tutorial Roundup.
Tags: Graph Theory, Jupyter, Python, Top tweets
- A Beginner’s Guide to Tweet Analytics with Pandas - Mar 29, 2017.
Unlike a lot of other tutorials which often pull from the real-time Twitter API, we will be using the downloadable Twitter Analytics data, and most of what we do will be done in Pandas.
Tags: Pandas, Python, Twitter
- Email Spam Filtering: An Implementation with Python and Scikit-learn - Mar 17, 2017.
This post is an overview of a spam filtering implementation using Python and Scikit-learn. The results of 2 classifiers are contrasted and compared: multinomial Naive Bayes and support vector machines.
Tags: Machine Learning, Python, scikit-learn
- Top KDnuggets tweets, Mar 08-14: In-depth introduction to Machine Learning in 15 hours of expert videos - Mar 15, 2017.
Also: #ICYMI The #DataScience Project Playbook; Every Intro to #DataScience Course on the Internet, Ranked; Quick reference to #Python in a single script.
Tags: Online Education, Python, Statistical Learning, Top tweets
- KDnuggets™ News 17:n10, Mar 15: Becoming a Data Science Unicorn; What Makes a Good Data Visualization? - Mar 15, 2017.
6 Business Concepts you need to become a Data Science Unicorn; What Makes a Good Data Visualization?; Best Data Science Courses from Udemy (only $19 till Mar 31); K-Means & Other Clustering Algorithms: A Quick Intro with Python; Free Online Data Science & Big Data Books
Tags: Big Data, Data Science, Data Visualization, Free ebook, K-means, MOOC, Python, Udemy, Unicorn
- Open Source Toolkits for Speech Recognition - Mar 14, 2017.
This article reviews the main options for free speech recognition toolkits that use traditional Hidden Markov Models and n-gram language models.
Tags: C++, Java, Open Source, Python, Speech Recognition, SVDS
- Best Data Science Courses from Udemy (only $19 till Mar 31) - Mar 10, 2017.
Here a list of the best courses in data science from Udemy, covering Data Science, Machine Learning, Python, Spark, Tableau, and Hadoop - only $19 until March 31, 2017.
Tags: Apache Spark, Hadoop, Machine Learning, Online Education, Python, Tableau, Udemy
- Working With Numpy Matrices: A Handy First Reference - Mar 10, 2017.
This introductory tutorial does a great job of outlining the most common Numpy array creation and manipulation functionality. A good post to keep handy while taking your first steps in Numpy, or to use as a handy reminder.
Tags: numpy, Python
- K-Means & Other Clustering Algorithms: A Quick Intro with Python - Mar 8, 2017.
In this intro cluster analysis tutorial, we'll check out a few algorithms in Python so you can get a basic understanding of the fundamentals of clustering on a real dataset.
Tags: Clustering, K-means, Python, scikit-learn
- KDnuggets™ News 17:n09, Mar 8: 7 More Steps to Mastering Machine Learning w. Python; Every Intro to Data Science Course, Ranked - Mar 8, 2017.
Also The Data Science Project Playbook; Hadoop Is Falling - Why? Bokeh Cheat Sheet: Data Visualization in Python
Tags: Bokeh, Data Science Education, Data Visualization, Hadoop, Machine Learning, Python
- A Simple XGBoost Tutorial Using the Iris Dataset - Mar 7, 2017.
This is an overview of the XGBoost machine learning algorithm, which is fast and shows good results. This example uses multiclass prediction with the Iris dataset from Scikit-learn.
Tags: Python, scikit-learn, XGBoost
- Bokeh Cheat Sheet: Data Visualization in Python - Mar 3, 2017.
Bokeh is the Python data visualization library that enables high-performance visual presentation of large datasets in modern web browsers. The package is flexible and offers lots of possibilities to visualize your data in a compelling way, but can be overwhelming.
Tags: Bokeh, Cheat Sheet, Data Visualization, DataCamp, Python
- Gartner Data Science Platforms – A Deeper Look - Mar 3, 2017.
Thomas Dinsmore critical examination of Gartner 2017 MQ of Data Science Platforms, including vendors who out, in, have big changes, Hadoop and Spark integration, open source software, and what Data Scientists actually use.
Tags: Apache Spark, Data Science Platform, Gartner, IBM, Python, R, SAS, Thomas Dinsmore
- Building a Bot to Answer FAQs: Predicting Text Similarity - Mar 2, 2017.
In this post, learn to build a bot to answer frequently asked questions, reducing lag time for more customers and taking the load off of engineers, ensuring they can concentrate on building products!
Tags: Chatbot, Python, Similarity
- Top KDnuggets tweets, Feb 22-28: 50 Companies Leading the #AI Revolution; #AI Nanodegree Program Syllabus - Mar 1, 2017.
50 Companies Leading the #AI Revolution; #AI Nanodegree Program Syllabus: Term 1, In Depth; What is a Support Vector Machine, and Why Would I Use it?; 6 Easy Steps to Learn Naive #Bayes Algorithm (with code in #Python).
Tags: AI, Bayesian, Online Education, Python, Reinforcement Learning, Top tweets, Udacity
7 More Steps to Mastering Machine Learning With Python - Mar 1, 2017.
This post is a follow-up to last year's introductory Python machine learning post, which includes a series of tutorials for extending your knowledge beyond the original.
Pages: 1 2
Tags: 7 Steps, Classification, Clustering, Deep Learning, Ensemble methods, Gradient Boosting, Machine Learning, Python, scikit-learn, Sebastian Raschka
- KDnuggets™ News 17:n08, Mar 1: Deep Learning Frameworks Dissected; Gartner Magic Quadrant for Data Science Platforms - Mar 1, 2017.
The Anatomy of Deep Learning Frameworks; Gartner 2017 Magic Quadrant for Data Science Platforms: gainers and losers; Data Science vs Fake News Contest; An Overview of Python Deep Learning Frameworks; Moving from R to Python: The Libraries You Need to Know
Tags: Data Science, Deep Learning, Fake News, Gartner, Magic Quadrant, Python, R
- What I Learned Implementing a Classifier from Scratch in Python - Feb 28, 2017.
In this post, the author implements a machine learning algorithm from scratch, without the use of a library such as scikit-learn, and instead writes all of the code in order to have a working binary classifier algorithm.
Tags: Classification, Machine Learning, Perceptron, Python, Sebastian Raschka
- An Overview of Python Deep Learning Frameworks - Feb 27, 2017.
Read this concise overview of leading Python deep learning frameworks, including Theano, Lasagne, Blocks, TensorFlow, Keras, MXNet, and PyTorch.
Tags: Deep Learning, Keras, Neural Networks, Python, TensorFlow, Theano, Torch
- The 6 Best Data Science Courses from Udemy (only $10 till Feb 28) - Feb 25, 2017.
Here a list of the best courses in data science from Udemy, covering Data Science, Machine Learning, Python, Spark, Tableau, and Hadoop - only $10 until Feb 28, 2017.
Tags: Apache Spark, Hadoop, Machine Learning, Online Education, Python, Tableau, Udemy
- Moving from R to Python: The Libraries You Need to Know - Feb 24, 2017.
Are you considering making a move from R to Python? Here are the libraries you need to know, how they stack up to their R contemporaries, and why you should learn them.
Tags: Jupyter, Pandas, Programming, Python, R, scikit-learn, Yhat
- What is a Support Vector Machine, and Why Would I Use it? - Feb 23, 2017.
Support Vector Machine has become an extremely popular algorithm. In this post I try to give a simple explanation for how it works and give a few examples using the the Python Scikits libraries.
Tags: Python, scikit-learn, Support Vector Machines, SVM, Yhat
- Introduction to Correlation - Feb 22, 2017.
Correlation is one of the most widely used (and widely misunderstood) statistical concepts. We provide the definitions and intuition behind several types of correlation and illustrate how to calculate correlation using the Python pandas library.
Tags: Beginners, Correlation, Datascience.com, Pandas, Python, Statistics
Removing Outliers Using Standard Deviation in Python - Feb 16, 2017.
Standard Deviation is one of the most underrated statistical tools out there. It’s an extremely useful metric that most people know how to calculate but very few know how to use effectively.
Tags: Applied Statistics, Outliers, Python, Statistics
- Apache Arrow and Apache Parquet: Why We Needed Different Projects for Columnar Data, On Disk and In-Memory - Feb 16, 2017.
Apache Parquet and Apache Arrow both focus on improving performance and efficiency of data analytics. These two projects optimize performance for on disk and in-memory processing
Tags: Apache, Apache Arrow, Apache Spark, Data Science, Dremio, In-Memory Computing, Machine Learning, Python
- KDnuggets™ News 17:n06, Feb 15: So What is Big Data? 52 Useful Machine Learning APIs; Data Science finds Perfect Valentines Dates - Feb 15, 2017.
Also Making Python Speak SQL with pandasql; 52 Useful Machine Learning & Prediction APIs, updated; New Poll: Do you support Trump Immigration Ban?
Tags: API, Big Data, Clustering, Data Science Platform, Machine Learning, Python, SQL
- Web Scraping for Dataset Curation, Part 2: Tidying Craft Beer Data - Feb 14, 2017.
This is the second part in a 2 part series on curating data from the web. The first part focused on web scraping, while this post details the process of tidying scraped data after the fact.
Tags: Beer, Data Curation, Dataset, Python
- Web Scraping for Dataset Curation, Part 1: Collecting Craft Beer Data - Feb 13, 2017.
This post is the first in a 2 part series on scraping and cleaning data from the web using Python. This first part is concerned with the scraping aspect, while the second part while focus on the cleaning. A concrete example is presented.
Tags: Beer, Data Curation, Dataset, Python
- Making Python Speak SQL with pandasql - Feb 8, 2017.
Want to wrangle Pandas data like you would SQL using Python? This post serves as an introduction to pandasql, and details how to get it up and running inside of Rodeo.
Tags: Pandas, Python, SQL, Yhat
- Top KDnuggets tweets, Jan 25-31: Python implementations of Andrew Ng #MachineLearning MOOC exercises - Feb 1, 2017.
#Python implementations of Andrew Ng #MachineLearning MOOC exercises; This repository contains the entire #Python #DataScience Handbook; What are the best #visualizations of #MachineLearning algorithms? Learn #TensorFlow and #DeepLearning, without a PhD.
Tags: Algorithms, Andrew Ng, Data Visualization, Machine Learning, Python, TensorFlow, Top tweets
- Domino Data Science Popup, San Francisco, Feb 22 – KDnuggets Offer - Jan 31, 2017.
Learn about the latest trends in data science applications in technology from the top experts in the industry. Register by Feb 8 and save with code KDNuggetsVIP.
Tags: Adversarial, CA, Domino, Paco Nathan, Python, San Francisco
Pandas Cheat Sheet: Data Science and Data Wrangling in Python - Jan 27, 2017.
The Pandas library can seem very elaborate and it might be hard to find a single point of entry to the material: with other learning materials focusing on different aspects of this library, you can definitely use a reference sheet to help you get the hang of it.
Tags: Cheat Sheet, Data Preparation, DataCamp, Pandas, Python
- Great Collection of Minimal and Clean Implementations of Machine Learning Algorithms - Jan 25, 2017.
Interested in learning machine learning algorithms by implementing them from scratch? Need a good set of examples to work from? Check out this post with links to minimal and clean implementations of various algorithms.
Tags: Algorithms, Machine Learning, Programming, Python
- Learn how to Develop and Deploy a Gradient Boosting Machine Model - Jan 20, 2017.
GBM is one the hottest machine learning methods. Learn how to create GBM using SciKit-Learn and Python and
understand the steps required to transform features, train, and deploy a GBM.
Tags: Gradient Boosting, Open Data Group, Python, scikit-learn
- Clean Data Science: Evaluating The Cleanliness of NYC Craft Beer Bar Kitchens - Jan 13, 2017.
An analysis of NYC Open Data health inspections showing that craft beer bar kitchens in Manhattan are cleaner than the average establishment by a statistically significant margin. An encouraging finding for Dry January.
Tags: Beer, Data Visualization, Food, New York City, NY, Open Data, Python
The Most Popular Language For Machine Learning and Data Science Is … - Jan 11, 2017.
When it comes to choosing programming language for Data Analytics projects or job prospects, people have different opinions depending on their career backgrounds and domains they worked in. Here is the analysis of data from indeed.com with respect to choice of programming language for machine learning and data science.
Tags: Data Science, Machine Learning, Programming Languages, Python, R, Scala
- Creating Data Visualization in Matplotlib - Jan 5, 2017.
Matplotlib is the most widely used data visualization library for Python; it's very powerful, but with a steep learning curve. This overview covers a selection of plots useful for a wide range of data analysis problems and discusses how to best deploy each one so you can tell your data story.
Tags: Data Visualization, Datascience.com, Matplotlib, Python
- Tidying Data in Python - Jan 4, 2017.
This post summarizes some tidying examples Hadley Wickham used in his 2014 paper on Tidy Data in R, but will demonstrate how to do so using the Python pandas library.
Tags: Data Cleaning, Data Preparation, Pandas, Python
- Supercharge Your Data Science Team with AnacondaCON Team Discount, till Jan 16 - Jan 3, 2017.
AnacondaCON '17 will help you conquer your biggest data science challenges. Learn from industry experts sharing what #OpenDataScienceMeans and their best practices. Get 2 for 1 ticket price thru Jan 16, 2017.
Tags: Anaconda, Austin, Data Science, Open Data Platform, Python, TX
- 5 Machine Learning Projects You Can No Longer Overlook, January - Jan 2, 2017.
There are a lot of popular machine learning projects out there, but many more that are not. Which of these are actively developed and worth checking out? Here is an offering of 5 such projects, the most recent in an ongoing series.
Tags: Boosting, C++, Data Preparation, Decision Trees, Machine Learning, Neural Networks, Optimization, Overlook, Pandas, Python, scikit-learn
- Over 600 data science, machine learning, Big Data eBooks/videos for only $5 (until Jan 9) - Dec 22, 2016.
Packt have more than 600 data science, analysis, machine learning and Big Data eBooks and video courses. And until Jan 9, 2017 every single one is available for just $5.
Tags: Big Data, Data Analysis, ebook, Packt Publishing, Python, R
- 3 ways to learn Data Science at Statistics.com - Dec 21, 2016.
Get the personal touch you need to deepen your learning with Statistics.com classes that are small, rich and engaging with readings, videos, quizzes, homework, and practical projects, taught online by leading instructors.
Tags: Data Analytics, Data Mining, Data Science Certificate, Online Education, Python, R, Statistics.com
- Top KDnuggets tweets, Dec 7-13: Want to learn Numpy? A Github repo of Numpy learning exercises - Dec 14, 2016.
Also Deep Learning Roadmap: "Which paper should I start reading from?"; Free ebooks: #MachineLearning with #Python and Practical Data Analysis; Daily plan for studying to become a Google software engineer.
Tags: Deep Learning, numpy, Python, Software Engineer, Top tweets
50+ Data Science, Machine Learning Cheat Sheets, updated - Dec 14, 2016.
Gear up to speed and have concepts and commands handy in Data Science, Data Mining, and Machine learning algorithms with these cheat sheets covering R, Python, Django, MySQL, SQL, Hadoop, Apache Spark, Matlab, and Java.
Tags: Cheat Sheet, Data Science, Django, Hadoop, Java, Machine Learning, MATLAB, Python, R
- Introduction to K-means Clustering: A Tutorial - Dec 9, 2016.
A beginner introduction to the widely-used K-means clustering algorithm, using a delivery fleet data example in Python.
Tags: Clustering, Datascience.com, K-means, Python
- KDnuggets Top Blogs and Bloggers in November 2016 - Dec 8, 2016.
We recognize the best KDnuggets Bloggers who had the most popular blogs by views or social media shares in November 2016.
Tags: Bayesian, Donald Trump, Machine Learning, Python, Top bloggers
