- Torus for Docker-First Data Science - May 8, 2018.
To help data science teams adopt Docker and apply DevOps best practices to streamline machine learning delivery pipelines, we open-sourced a toolkit based on the popular cookiecutter project structure.
Data Science, DevOps, Docker, Machine Learning Engineer, Open Source, Python
- How I Used CNNs and Tensorflow and Lost a Silver Medal in Kaggle Challenge - May 8, 2018.
I joined the competition a month before it ended, eager to explore how to use Deep Natural Language Processing (NLP) techniques for this problem. Then came the deception. And I will tell you how I lost my silver medal in that competition.
Convolutional Neural Networks, Kaggle, Neural Networks, Python, TensorFlow
- Top Data Science, Machine Learning Courses from Udemy – May 2018 - May 8, 2018.
Learn Machine Learning, Data Science, Python, Azure Machine Learning, and more with Udemy Mother's Day $9.99 sale - get top courses from leading instructors.
Azure ML, Data Science, Machine Learning, Python, Udemy
Apache Spark : Python vs. Scala - May 4, 2018.
When it comes to using the Apache Spark framework, the data science community is divided in two camps; one which prefers Scala whereas the other preferring Python. This article compares the two, listing their pros and cons.
Apache Spark, Java, Python, Scala
Boost your data science skills. Learn linear algebra. - May 3, 2018.
The aim of these notebooks is to help beginners/advanced beginners to grasp linear algebra concepts underlying deep learning and machine learning. Acquiring these skills can boost your ability to understand and apply various data science algorithms.
Data Science, Linear Algebra, Mathematics, numpy, Python
- Hands-on: Intro to Python for Data Analysis - May 2, 2018.
Learn one of the top languages used in data science and machine learning with this new hands-on course by TDWI Online Learning.
Data Analysis, Online Education, Python, TDWI
- Getting Started with spaCy for Natural Language Processing - May 2, 2018.
spaCy is a Python natural language processing library specifically designed with the goal of being a useful library for implementing production-ready systems. It is particularly fast and intuitive, making it a top contender for NLP tasks.
Data Preparation, Data Preprocessing, NLP, Python, Text Analytics, Text Mining
- KDnuggets™ News 18:n18, May 2: Blockchain Explained in 7 Python Functions; Data Science Dirty Secret; Choosing the Right Evaluation Metric - May 2, 2018.
Also: Building Convolutional Neural Network using NumPy from Scratch; Data Science Interview Guide; Implementing Deep Learning Methods and Feature Engineering for Text Data: The GloVe Model; Jupyter Notebook for Beginners: A Tutorial
Blockchain, Convolutional Neural Networks, Data Science, Machine Learning, Metrics, numpy, Python
- Jupyter Notebook for Beginners: A Tutorial - May 1, 2018.
The Jupyter Notebook is an incredibly powerful tool for interactively developing and presenting data science projects. Although it is possible to use many different programming languages within Jupyter Notebooks, this article will focus on Python as it is the most common use case.
Pages: 1 2
Data Analysis, GitHub, Jupyter, Matplotlib, Python
- Implementing Deep Learning Methods and Feature Engineering for Text Data: FastText - May 1, 2018.
Overall, FastText is a framework for learning word representations and also performing robust, fast and accurate text classification. The framework is open-sourced by Facebook on GitHub.
Facebook, Feature Engineering, NLP, Python
- Pair Finance: Python Developer - Apr 30, 2018.
Seeking a Python Developer to work on a completely new and innovative product we are building, along with a small team of other experienced developers, and to collaborate on an iterative design process from a basic prototype to the first production version.
Berlin, Developer, Germany, Pair Finance, Python
Choosing the Right Metric for Evaluating Machine Learning Models – Part 1 - Apr 27, 2018.
Each machine learning model is trying to solve a problem with a different objective using a different dataset and hence, it is important to understand the context before choosing a metric.
Machine Learning, Metrics, Python, Regression
Blockchain Explained in 7 Python Functions - Apr 27, 2018.
It wasn’t until I wrote my own simple Blockchain, that I truly understood what it is and the potential applications for it. So without further ado, lets set up our 7 functions!
Blockchain, Encryption, Python
- Building Convolutional Neural Network using NumPy from Scratch - Apr 26, 2018.
In this article, CNN is created using only NumPy library. Just three layers are created which are convolution (conv for short), ReLU, and max pooling.
Convolutional Neural Networks, Image Recognition, Neural Networks, numpy, Python
- Implementing Deep Learning Methods and Feature Engineering for Text Data: The GloVe Model - Apr 25, 2018.
The GloVe model stands for Global Vectors which is an unsupervised learning model which can be used to obtain dense word vectors similar to Word2Vec.
Deep Learning, Feature Engineering, NLP, Python, Text Mining
- KDnuggets™ News 18:n17, Apr 25: Python Regular Expressions Cheat Sheet; Deep Learning With Apache Spark; Building a Question Answering Model - Apr 25, 2018.
Also: Derivation of Convolutional Neural Network from Fully Connected Network Step-By-Step; Presto for Data Scientists - SQL on anything; Why Deep Learning is perfect for NLP (Natural Language Processing); Top 16 Open Source Deep Learning Libraries and Platforms
Apache Spark, Cheat Sheet, Deep Learning, NLP, Python, Question answering, SQL
- How I Unknowingly Contributed To Open Source - Apr 24, 2018.
This article explains what is meant by the term 'open source' and why all data scientists should be a part of it.
fast.ai, GitHub, Jeremy Howard, Open Source, Python, scikit-learn
- Swiftapply – Automatically efficient pandas apply operations - Apr 24, 2018.
Using Swiftapply, easily apply any function to a pandas dataframe in the fastest available manner.
Pandas, Python
- Neural Network based Startup Name Generator - Apr 20, 2018.
How to build a recurrent neural network to generate suggestions for your new company’s name.
Neural Networks, Python, Startups
- Python Regular Expressions Cheat Sheet - Apr 19, 2018.
The tough thing about learning data is remembering all the syntax. While at Dataquest we advocate getting used to consulting the Python documentation, sometimes it's nice to have a handy reference, so we've put together this cheat sheet to help you out!
Cheat Sheet, Programming, Python, Text Analytics
- Robust Word2Vec Models with Gensim & Applying Word2Vec Features for Machine Learning Tasks - Apr 17, 2018.
The gensim framework, created by Radim Řehůřek consists of a robust, efficient and scalable implementation of the Word2Vec model.
Feature Engineering, NLP, Python, Word Embeddings, word2vec
- Getting Started with PyTorch Part 1: Understanding How Automatic Differentiation Works - Apr 11, 2018.
PyTorch has emerged as a major contender in the race to be the king of deep learning frameworks. What makes it really luring is it’s dynamic computation graph paradigm.
Pages: 1 2
Deep Learning, Neural Networks, Python, PyTorch
- Implementing Deep Learning Methods and Feature Engineering for Text Data: The Skip-gram Model - Apr 10, 2018.
Just like we discussed in the CBOW model, we need to model this Skip-gram architecture now as a deep learning classification model such that we take in the target word as our input and try to predict the context words.
Deep Learning, Feature Engineering, NLP, Python, Text Mining, Word Embeddings
- Top Data Science, Machine Learning Courses from Udemy – April 2018 - Apr 5, 2018.
Udemy April $10.99 sale is now going on top courses from leading instructors and learn Machine Learning, Data Science, Python, Azure Machine Learning, and more.
Azure ML, Data Science, Machine Learning, Python, Udemy
- Why You Should Start Using .npy Files More Often - Apr 3, 2018.
In this article, we demonstrate the utility of using native NumPy file format .npy over CSV for reading large numerical data set. It may be an useful trick if the same CSV data file needs to be read many times.
numpy, Python
- Using Tensorflow Object Detection to do Pixel Wise Classification - Mar 29, 2018.
Tensorflow recently added new functionality and now we can extend the API to determine pixel by pixel location of objects of interest. So when would we need this extra granularity?
Classification, Image Recognition, Object Detection, Python, TensorFlow
- Understanding Feature Engineering: Deep Learning Methods for Text Data - Mar 28, 2018.
Newer, advanced strategies for taming unstructured, textual data: In this article, we will be looking at more advanced feature engineering strategies which often leverage deep learning models.
Deep Learning, Feature Engineering, NLP, Python, Text Mining
Text Data Preprocessing: A Walkthrough in Python - Mar 26, 2018.
This post will serve as a practical walkthrough of a text data preprocessing task using some common Python tools.
Data Preparation, Data Preprocessing, NLP, Python, Text Analytics, Text Mining
- Quick Feature Engineering with Dates Using fast.ai - Mar 16, 2018.
The fast.ai library is a collection of supplementary wrappers for a host of popular machine learning libraries, designed to remove the necessity of writing your own functions to take care of some repetitive tasks in a machine learning workflow.
fast.ai, Feature Engineering, Machine Learning, Pandas, Python, Time Series
- Web Scraping with Python: Illustration with CIA World Factbook - Mar 16, 2018.
In this article, we show how to use Python libraries and HTML parsing to extract useful information from a website and answer some important analytics questions afterwards.
Analytics, CIA, Python, Web Scraping
- Creating a simple text classifier using Google CoLaboratory - Mar 15, 2018.
Google CoLaboratory is Google’s latest contribution to AI, wherein users can code in Python using a Chrome browser in a Jupyter-like environment. In this article I have shared a method, and code, to create a simple binary text classifier using Scikit Learn within Google CoLaboratory environment.
Google, Google Colab, Jupyter, Python, Text Classification
- A Beginner’s Guide to Data Engineering – Part II - Mar 15, 2018.
In this post, I share more technical details on how to build good data pipelines and highlight ETL best practices. Primarily, I will use Python, Airflow, and SQL for our discussion.
Pages: 1 2
AirBnB, Data Engineering, Data Science, ETL, Pipeline, Python, SQL
Top 5 Best Jupyter Notebook Extensions - Mar 13, 2018.
Check out these 5 Jupyter notebook extensions to help increase your productivity.
Jupyter, Python
- Top Data Science, Machine Learning Courses from Udemy – March 2018 - Mar 12, 2018.
Udemy St Patrick's Day $11.99 sale on top courses from leading instructors and learn Machine Learning, Data Science, Python, Azure Machine Learning, and more.
Azure ML, Data Science, Machine Learning, Python, Udemy
- KDnuggets™ News 18:n10, Mar 7: Functional Programming in Python; Surviving Your Data Science Interview; Easy Image Recognition with Google Tensorflow - Mar 7, 2018.
Also: Data Science in Fashion; Time Series for Dummies - The 3 Step Process; Deep Misconceptions About Deep Learning; Data Science for Javascript Developers
Data Science, Deep Learning, Functional Programming, Image Recognition, Interview, Javascript, Python, TensorFlow, Time Series
- TDWI Chicago, May 6-11: Get Your Hands Dirty With Data – KDnuggets Offer - Mar 2, 2018.
Attend the Hands-on Lab series and bring practical skills back from Chicago. Save 30% through March 16 with priority code KD30.
Chicago, Hadoop, IL, Machine Learning, Python, R, TDWI, Training
- Unleash a faster Python on your data - Mar 1, 2018.
Get real performance results and download the free Intel Distribution for Python that includes everything you need for blazing-fast computing, analytics, machine learning, and more.
Data Analytics, HPC, Intel, Performance, Python
- Top KDnuggets tweets, Feb 21-27: Top 20 Python #AI and #MachineLearning Open Source Projects; Intro to Reinforcement Learning Algorithms - Feb 28, 2018.
Also: #NeuralNetwork #AI is simple. So... Stop pretending; 5 Free Resources for Getting Started with #DeepLearning for Natural Language Pro; Want a Job in #Data? Learn This
Deep Learning, Machine Learning, NLP, Python, Reinforcement Learning, Top tweets
Introduction to Functional Programming in Python - Feb 28, 2018.
Python facilitates different approaches to writing code, and while an object-oriented approach is common, an alternative and useful style of writing code is functional programming.
Pages: 1 2
Functional Programming, Programming, Python
- 5 Fantastic Practical Natural Language Processing Resources - Feb 22, 2018.
This post presents 5 practical resources for getting a start in natural language processing, covering a wide array of topics and approaches.
Deep Learning, Keras, LSTM, Neural Networks, NLP, NLTK, Python
Top 20 Python AI and Machine Learning Open Source Projects - Feb 20, 2018.
We update the top AI and Machine Learning projects in Python. Tensorflow has moved to the first place with triple-digit growth in contributors. Scikit-learn dropped to 2nd place, but still has a very large base of contributors.
GitHub, Machine Learning, Open Source, Python, scikit-learn, TensorFlow
Deep Learning Development with Google Colab, TensorFlow, Keras & PyTorch - Feb 20, 2018.
Now you can develop deep learning applications with Google Colaboratory - on the free Tesla K80 GPU - using Keras, Tensorflow and PyTorch.
Pages: 1 2
Deep Learning, Google, Google Colab, Keras, Python, PyTorch, TensorFlow
- KDnuggets™ News 18:n07, Feb 14: 5 Machine Learning Projects You Should Not Overlook; Intro to Python Ensembles - Feb 14, 2018.
5 Machine Learning Projects You Should Not Overlook; Introduction to Python Ensembles; Which Machine Learning Algorithm be used in year 2118?; Fast.ai Lesson 1 on Google Colab (Free GPU)
Algorithms, Data Science, Ensemble Methods, fast.ai, Feature Engineering, Google Colab, Machine Learning, Python, Scala
3 Essential Google Colaboratory Tips & Tricks - Feb 12, 2018.
Google Colaboratory is a promising machine learning research platform. Here are 3 tips to simplify its usage and facilitate using a GPU, installing libraries, and uploading data files.
Google, Google Colab, Python, TensorFlow, Tips
- Introduction to Python Ensembles - Feb 9, 2018.
In this post, we'll take you through the basics of ensembles — what they are and why they work so well — and provide a hands-on tutorial for building basic ensembles.
Pages: 1 2
Decision Trees, Ensemble Methods, Machine Learning, Python, random forests algorithm, ROC-AUC, scikit-learn, XGBoost
- 5 Machine Learning Projects You Should Not Overlook - Feb 8, 2018.
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!
Bayesian, Gradient Boosting, Keras, Machine Learning, Overlook, PHP, Python, scikit-learn
- KDnuggets™ News 18:n06, Feb 7: 5 Fantastic Practical Machine Learning Resources; 8 Must-Know Neural Network Architectures - Feb 7, 2018.
5 Fantastic Practical Machine Learning Resources; The 8 Neural Network Architectures Machine Learning Researchers Need to Learn; Generalists Dominate Data Science; Avoid Overfitting with Regularization; Understanding Learning Rates and How It Improves Performance in Deep Learning
Architecture, Data Science, Machine Learning, Neural Networks, Overfitting, Python, Regularization, Web Scraping
- 2018 Predictions for the Analytics & Data Science Hiring Market - Feb 6, 2018.
What do you think of this year’s predictions? Do you see any new tools on the horizon, or do you believe data science popularity is due for a reckoning of sorts?
2018 Predictions, AI, Automation, Burtch Works, China, Data Scientist, Hiring, Python
- 5 Fantastic Practical Machine Learning Resources - Feb 6, 2018.
This post presents 5 fantastic practical machine learning resources, covering machine learning right from basics, as well as coding algorithms from scratch and using particular deep learning frameworks.
Deep Learning, fast.ai, Gluon, Machine Learning, MOOC, MXNet, Python
- A Simple Starter Guide to Build a Neural Network - Feb 5, 2018.
This guide serves as a basic hands-on work to lead you through building a neural network from scratch. Most of the mathematical concepts and scientific decisions are left out.
Machine Learning, Neural Networks, Python, PyTorch
- Web Scraping Tutorial with Python: Tips and Tricks - Feb 1, 2018.
This post is intended for people who are interested to know about the common design patterns, pitfalls and rules related to the web scraping.
BeautifulSoup, Python, Tips, Web Scraping
- Using AutoML to Generate Machine Learning Pipelines with TPOT - Jan 29, 2018.
This post will take a different approach to constructing pipelines. Certainly the title gives away this difference: instead of hand-crafting pipelines and hyperparameter optimization, and performing model selection ourselves, we will instead automate these processes.
Automated Machine Learning, Hyperparameter, Optimization, Pipeline, Python, scikit-learn, Workflow
- Managing Machine Learning Workflows with Scikit-learn Pipelines Part 3: Multiple Models, Pipelines, and Grid Searches - Jan 24, 2018.
In this post, we will be using grid search to optimize models built from a number of different types estimators, which we will then compare and properly evaluate the best hyperparameters that each model has to offer.
Data Preprocessing, Hyperparameter, Optimization, Pipeline, Python, scikit-learn, Workflow
- Using Excel with Pandas - Jan 23, 2018.
In this tutorial, we are going to show you how to work with Excel files in pandas, covering computer setup, reading in data from Excel files into pandas, data exploration in pandas, and more.
Pages: 1 2
Excel, Histogram, Pandas, Python
- Using Genetic Algorithm for Optimizing Recurrent Neural Networks - Jan 22, 2018.
In this tutorial, we will see how to apply a Genetic Algorithm (GA) for finding an optimal window size and a number of units in Long Short-Term Memory (LSTM) based Recurrent Neural Network (RNN).
Automated Machine Learning, Genetic Algorithm, Keras, Neural Networks, Python, Recurrent Neural Networks
- Managing Machine Learning Workflows with Scikit-learn Pipelines Part 2: Integrating Grid Search - Jan 19, 2018.
Another simple yet powerful technique we can pair with pipelines to improve performance is grid search, which attempts to optimize model hyperparameter combinations.
Data Preprocessing, Hyperparameter, Optimization, Pipeline, Python, scikit-learn, Workflow
- Are you monitoring your machine learning systems? - Jan 18, 2018.
How are you monitoring your Python applications? Take the short survey - the results will be published on KDnuggets and you will get all the details.
Machine Learning, Monitoring, Python, Survey
- Gradient Boosting in TensorFlow vs XGBoost - Jan 18, 2018.
For many Kaggle-style data mining problems, XGBoost has been the go-to solution since its release in 2016. It's probably as close to an out-of-the-box machine learning algorithm as you can get today.
Gradient Boosting, Python, TensorFlow, XGBoost
- Is Learning Rate Useful in Artificial Neural Networks? - Jan 15, 2018.
This article will help you understand why we need the learning rate and whether it is useful or not for training an artificial neural network. Using a very simple Python code for a single layer perceptron, the learning rate value will get changed to catch its idea.
Hyperparameter, Neural Networks, Python
- Top Data Science, Machine Learning Courses from Udemy - Jan 5, 2018.
Enjoy the New Year sale on top courses from leading instructors and learn Machine Learning, Data Science, Python, Azure Machine Learning, and more.
Azure ML, Data Science, Machine Learning, Python, Udemy
- Simple Ways Of Working With Medium To Big Data Locally - Dec 27, 2017.
An overview of the installation and implementation of simple techniques for working with large datasets in your machine.
Big Data, iPhone, Python, R, SAS
- Top KDnuggets tweets, Dec 13-19: The Art of Learning Data Science; Data Science, ML Main Developments, Key Trends - Dec 20, 2017.
The Art of Learning #DataScience; How to Generate FiveThirtyEight Graphs in #Python; #TensorFlow for Short-Term Stocks Prediction; 15 Mathematics MOOCs for #DataScience.
Data Science, Data Visualization, Python, TensorFlow, Top tweets
- KDnuggets™ News 17:n48, Dec 20: Machine Learning 2017 Key Trends; New Poll: When is AGI Coming?; AI Year End Roundup - Dec 20, 2017.
Machine Learning & Artificial Intelligence: Main Developments in 2017 and Key Trends in 2018; New Poll: When will Artificial General Intelligence (AGI) be achieved?; Xavier Amatriain's Machine Learning and Artificial Intelligence Year-end Roundup; How to Generate FiveThirtyEight Graphs in Python; Transitioning to Data Science: How to become a data scientist
2018 Predictions, AGI, AI, Data Science, Data Visualization, FiveThirtyEight, Machine Learning, Poll, Python
- $5 Data science eBooks and videos from Packt - Dec 19, 2017.
Check Packt $5 sale on every ebook and video, including many great titles on Data Analysis, Machine Learning, Python, Deep Learning, and more - sale runs until Jan 15, 2018.
Machine Learning, Packt Publishing, Python, Sebastian Raschka
- Getting Started with TensorFlow: A Machine Learning Tutorial - Dec 19, 2017.
A complete and rigorous introduction to Tensorflow. Code along with this tutorial to get started with hands-on examples.
Pages: 1 2
Machine Learning, Python, TensorFlow
- Accelerating Algorithms: Considerations in Design, Algorithm Choice and Implementation - Dec 18, 2017.
If you are trying to make your algorithms run faster, you may want to consider reviewing some important points on design and implementation.
ActiveState, Algorithms, Implementation, Python
- Building an Audio Classifier using Deep Neural Networks - Dec 15, 2017.
Using a deep convolutional neural network architecture to classify audio and how to effectively use transfer learning and data-augmentation to improve model accuracy using small datasets.
Acoustics, Audio, Deep Learning, Python, Speech, Speech Recognition, Transfer Learning
- Best Data Science, Machine Learning Courses from Udemy, only $10 until Dec 21 - Dec 14, 2017.
Holiday Dev & IT sale on best courses from Udemy, including Data Science, Machine Learning, Python, Spark, Tableau, and Hadoop - only $10 until Dec 21, 2017.
Apache Spark, Hadoop, Machine Learning, Online Education, Python, Tableau, Udemy
- How to Generate FiveThirtyEight Graphs in Python - Dec 14, 2017.
In this post, we'll help you. Using Python's matplotlib and pandas, we'll see that it's rather easy to replicate the core parts of any FiveThirtyEight (FTE) visualization.
Data Visualization, Dataquest, FiveThirtyEight, Python
- TensorFlow for Short-Term Stocks Prediction - Dec 12, 2017.
In this post you will see an application of Convolutional Neural Networks to stock market prediction, using a combination of stock prices with sentiment analysis.
Convolutional Neural Networks, Finance, Python, Stocks, TensorFlow
- Robust Algorithms for Machine Learning - Dec 11, 2017.
This post mentions some of the advantages of implementing robust, non-parametric methods into our Machine Learning frameworks and models.
ActiveState, Keras, Machine Learning, Python, Statistics
- Today I Built a Neural Network During My Lunch Break with Keras - Dec 8, 2017.
So yesterday someone told me you can build a (deep) neural network in 15 minutes in Keras. Of course, I didn’t believe that at all. So the next day I set out to play with Keras on my own data.
Keras, Neural Networks, Python
- Unleash a faster Python on your data - Dec 7, 2017.
Get real performance results and download the free Intel® Distribution for Python that includes everything you need for blazing-fast computing, analytics, machine learning, and more. Use Intel Python with existing code, and you’re all set for a significant performance boost.
Analytics, Data Science, HPC, Intel, Python, Scientific Computing
- Managing Machine Learning Workflows with Scikit-learn Pipelines Part 1: A Gentle Introduction - Dec 7, 2017.
Scikit-learn's Pipeline class is designed as a manageable way to apply a series of data transformations followed by the application of an estimator.
Data Preprocessing, Pipeline, Python, scikit-learn, Workflow
- Web Scraping for Data Science with Python - Dec 6, 2017.
We take a quick look at how web scraping can be useful in the context of data science projects, eg to construct a social graph based of S&P 500 companies, using Python and Gephi.
Bart Baesens, Data Science, Python, S&P 500, Web Mining, Web Scraping
- Exploring Recurrent Neural Networks - Dec 1, 2017.
We explore recurrent neural networks, starting with the basics, using a motivating weather modeling problem, and implement and train an RNN in TensorFlow.
Neural Networks, Packt Publishing, Python, Recurrent Neural Networks, TensorFlow
- Machine Learning with Optimus on Apache Spark - Nov 30, 2017.
The way most Machine Learning models work on Spark are not straightforward, and they need lots of feature engineering to work. That’s why we created the feature engineering section inside the Optimus Data Frame Transformer.
Pages: 1 2
Apache Spark, Data Science, Feature Engineering, Machine Learning, MLlib, Python, Workflow
Why You Should Forget ‘for-loop’ for Data Science Code and Embrace Vectorization - Nov 29, 2017.
Data science needs fast computation and transformation of data. NumPy objects in Python provides that advantage over regular programming constructs like for-loop. How to demonstrate it in few easy lines of code?
numpy, Python, Scientific Computing
- How To Unit Test Machine Learning Code - Nov 28, 2017.
One of the main principles I learned during my time at Google Brain was that unit tests can make or break your algorithm and can save you weeks of debugging and training time.
Machine Learning, Neural Networks, Python, Software Engineering, TensorFlow
- Taming the Python Visualization Jungle, Nov 29 Webinar - Nov 22, 2017.
Python has a ton of plotting libraries—but which ones should you use? And how should you go about choosing them? This webinar shows you key starting points and demonstrates how to solve a range of common problems.
Anaconda, Data Visualization, Python
- How (& Why) Data Scientists and Data Engineers Should Share a Platform - Nov 17, 2017.
Sharing one platform has some obvious benefits for Data Science and Data Engineering teams, but technical, language and process challenges often make this a challenge. Learn how one company implemented single cloud platform for R, Python and other workloads – and some of the unexpected benefits they discovered along the way.
Apache Spark, Cazena, Data Science Platform, Hadoop, Python, R
- Best Data Science, Machine Learning Courses from Udemy, only $10 until Nov 28- Black Friday/Cybermonday sale - Nov 17, 2017.
Black Friday/Cybermonday sale on best courses from Udemy, including Data Science, Machine Learning, Python, Spark, Tableau, and Hadoop - only $10 until Nov 28, 2017.
Apache Spark, Hadoop, Machine Learning, Online Education, Python, Tableau, Udemy
Top 10 Videos on Deep Learning in Python - Nov 17, 2017.
Playlists, individual tutorials (not part of a playlist) and online courses on Deep Learning (DL) in Python using the Keras, Theano, TensorFlow and PyTorch libraries. Assumes no prior knowledge. These videos cover all skill levels and time constraints!
Deep Learning, Keras, Python, PyTorch, TensorFlow, Theano, Top 10, Tutorials, Videolectures, Youtube
- The Python Graph Gallery - Nov 16, 2017.
Welcome to the Python Graph Gallery, a website that displays hundreds of python charts with their reproducible code snippets.
Data Visualization, Matplotlib, Python, Seaborn
- PySpark SQL Cheat Sheet: Big Data in Python - Nov 16, 2017.
PySpark is a Spark Python API that exposes the Spark programming model to Python - With it, you can speed up analytic applications. With Spark, you can get started with big data processing, as it has built-in modules for streaming, SQL, machine learning and graph processing.
Pages: 1 2
Apache Spark, Big Data, DataCamp, Python, SQL
- TensorFlow: What Parameters to Optimize? - Nov 9, 2017.
Learning TensorFlow Core API, which is the lowest level API in TensorFlow, is a very good step for starting learning TensorFlow because it let you understand the kernel of the library. Here is a very simple example of TensorFlow Core API in which we create and train a linear regression model.
Neural Networks, Optimization, Python, TensorFlow
- Top KDnuggets tweets, Nov 01-07: Airbnb develops an #AI which converts design into source code - Nov 8, 2017.
Also: One LEGO at a time: Explaining the #Math of How #NeuralNetworks Learn; 6 Books Every #DataScientist Should Keep Nearby; Direct from Sebastian Raschka #Python #MachineLearning book, new edition.
AI, AirBnB, Books, Machine Learning, Neural Networks, Python, Sebastian Raschka, Top tweets
- Tips for Getting Started with Text Mining in R and Python - Nov 8, 2017.
This article opens up the world of text mining in a simple and intuitive way and provides great tips to get started with text mining.
Python, R, Text Mining
7 Steps to Mastering Deep Learning with Keras - Oct 30, 2017.
Are you interested in learning how to use Keras? Do you already have an understanding of how neural networks work? Check out this lean, fat-free 7 step plan for going from Keras newbie to master of its basics as quickly as is possible.
7 Steps, Convolutional Neural Networks, Deep Learning, Keras, Logistic Regression, LSTM, Machine Learning, Neural Networks, Python, Recurrent Neural Networks
- Best Data Science, Machine Learning Courses from Udemy (only $12 until Oct 31) - Oct 27, 2017.
Fall sale on best courses from Udemy, including Data Science, Machine Learning, Python, Spark, Tableau, and Hadoop - only $12 until Oct 31, 2017.
Apache Spark, Hadoop, Machine Learning, Online Education, Python, Tableau, Udemy
Ranking Popular Deep Learning Libraries for Data Science - Oct 23, 2017.
We rank 23 open-source deep learning libraries that are useful for Data Science. The ranking is based on equally weighing its three components: Github and Stack Overflow activity, as well as Google search results.
Caffe, Deep Learning, Keras, Python, PyTorch, TensorFlow, Theano
- 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.
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
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.
AI, Chatbot, 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
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!
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.
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.
Pages: 1 2
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.
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.
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.
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.
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
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.
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.
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.
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.
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.
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.
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?
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.
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.
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.
ActiveState, Intel, Production, Python
- 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.
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.
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.
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.
Algorithms, Data Science, GitHub, NLP, Python, Search, 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
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.
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.
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.
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.
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
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.
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.
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.
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.
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
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
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.
Andrew Ng, Machine Learning, Python
