Tag: Python (514)

• Explaining the 68-95-99.7 rule for a Normal Distribution - Jul 19, 2018.
  
  This post explains how those numbers were derived in the hope that they can be more interpretable for your future endeavors.

  Tags: Data Analysis, Data Science, Python, Statistics

• 5 Quick and Easy Data Visualizations in Python with Code - Jul 18, 2018.
  
  This post provides an overview of a small number of widely used data visualizations, and includes code in the form of functions to implement each in Python using Matplotlib.

  Tags: Data Visualization, Matplotlib, Python

• Basic Image Data Analysis Using Numpy and OpenCV, Part 2 - Jul 17, 2018.
  
  We explain how to easily access and manipulate the internal components of digital images using Python and give examples from satellite image processing.

  Tags: Computer Vision, Image Processing, numpy, OpenCV, Python

• KDnuggets™ News 18:n26, Jul 11: 5 Favorite Free Visualization Tools; SQL Cheat Sheet; Top 20 Python Libraries for Data Science - Jul 11, 2018.
  
  Also Introduction to Apache Spark; fast.ai Machine Learning Course Notes; Cartoon: How is Data Science Different From Religion?

  Tags: Cheat Sheet, Data Visualization, Python, SQL

• Basic Image Data Analysis Using Numpy and OpenCV – Part 1 - Jul 10, 2018.
  
  Accessing the internal component of digital images using Python packages becomes more convenient to understand its properties as well as nature.

  Tags: Computer Vision, Image Processing, numpy, OpenCV, Python

• Analyze a Soccer (Football) Game Using Tensorflow Object Detection and OpenCV - Jul 10, 2018.
  
  For the data scientist within you let's use this opportunity to do some analysis on soccer clips. With the use of deep learning and opencv we can extract interesting insights from video clips

  Tags: Football, Image Recognition, OpenCV, Python, Soccer, TensorFlow, Video recognition, World Cup

• Manage your Machine Learning Lifecycle with MLflow  –  Part 1 - Jul 5, 2018.
  
  Reproducibility, good management and tracking experiments is necessary for making easy to test other’s work and analysis. In this first part we will start learning with simple examples how to record and query experiments, packaging Machine Learning models so they can be reproducible and ran on any platform using MLflow.

  Tags: Databricks, Life Cycle, Pipeline, Python, Workflow

• Text Classification & Embeddings Visualization Using LSTMs, CNNs, and Pre-trained Word Vectors - Jul 5, 2018.
  
  In this tutorial, I classify Yelp round-10 review datasets. After processing the review comments, I trained three model in three different ways and obtained three word embeddings.

  Tags: Convolutional Neural Networks, Keras, LSTM, NLP, Python, Text Classification, Word Embeddings

• Deep Quantile Regression - Jul 3, 2018.
  
  Most Deep Learning frameworks currently focus on giving a best estimate as defined by a loss function. Occasionally something beyond a point estimate is required to make a decision. This is where a distribution would be useful. This article will purely focus on inferring quantiles.

  Tags: Deep Learning, Hyperparameter, Keras, Neural Networks, Python, Regression

• Inside the Mind of a Neural Network with Interactive Code in Tensorflow - Jun 29, 2018.
  
  Understand the inner workings of neural network models as this post covers three related topics: histogram of weights, visualizing the activation of neurons, and interior / integral gradients.

  Pages: 1 2

  Tags: Convolutional Neural Networks, Image Recognition, Neural Networks, Python, TensorFlow

• Building a Basic Keras Neural Network Sequential Model - Jun 29, 2018.
  
  The approach basically coincides with Chollet's Keras 4 step workflow, which he outlines in his book "Deep Learning with Python," using the MNIST dataset, and the model built is a Sequential network of Dense layers. A building block for additional posts.

  Tags: Keras, MNIST, Neural Networks, Python

• Top 20 Python Libraries for Data Science in 2018 - Jun 27, 2018.
  
  Our selection actually contains more than 20 libraries, as some of them are alternatives to each other and solve the same problem. Therefore we have grouped them as it's difficult to distinguish one particular leader at the moment.

  Pages: 1 2

  Tags: Bokeh, Data Science, Keras, Matplotlib, NLTK, numpy, Pandas, Plotly, Python, PyTorch, scikit-learn, SciPy, Seaborn, TensorFlow, XGBoost

• How to Execute R and Python in SQL Server with Machine Learning Services - Jun 25, 2018.
  
  Machine Learning Services in SQL Server eliminates the need for data movement - you can install and run R/Python packages to build Deep Learning and AI applications on data in SQL Server.

  Tags: Azure ML, Machine Learning, Microsoft, Python, R, SQL, SQL Server

• Get Packt Skill Up Developer Skills Report - Jun 19, 2018.
  
  Find the top tools for 4 distinct industries, learn what do developers in different sectors say is the next big thing, and more. Also get any Packt book or video for just $10.

  Tags: Developers, Free ebook, Machine Learning, Packt Publishing, Python

• Choosing the Right Metric for Evaluating Machine Learning Models — Part 2 - Jun 19, 2018.
  
  This will focus on commonly used metrics in classification, why should we prefer some over others with context.

  Tags: Classification, Machine Learning, Metrics, Python

• Step Forward Feature Selection: A Practical Example in Python - Jun 18, 2018.
  
  When it comes to disciplined approaches to feature selection, wrapper methods are those which marry the feature selection process to the type of model being built, evaluating feature subsets in order to detect the model performance between features, and subsequently select the best performing subset.

  Tags: Feature Selection, Machine Learning, Python

• Generating Text with RNNs in 4 Lines of Code - Jun 14, 2018.
  
  Want to generate text with little trouble, and without building and tuning a neural network yourself? Let's check out a project which allows you to "easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code."

  Tags: Donald Trump, LSTM, NLP, Python, Recurrent Neural Networks, Twitter

• KDnuggets™ News 18:n23, Jun 13: Did Python declare victory over R?; Master the Netflix Interview; Deep Learning Projects DIY Style - Jun 13, 2018.
  
  Also: Command Line Tricks For Data Scientists; How (dis)similar are my train and test data?; 5 Machine Learning Projects You Should Not Overlook, June 2018; Introduction to Game Theory; Human Interpretable Machine Learning

  Tags: Data Science, Deep Learning, Interview questions, Machine Learning, Netflix, Python, R, Training Data

• Empowering National Grid with Anaconda Enterprise - Jun 11, 2018.
  
  With Anaconda Enterprise, National Grid was able to implement a more informed and cost-effective system that allowed for greater accuracy in modeling and predicting maintenance needs. Read the case study to learn more.

  Tags: Anaconda, Electricity, Enterprise, National Grid, Python

• Packaging and Distributing Your Python Project to PyPI for Installation Using pip - Jun 11, 2018.
  
  This tutorial will explain the steps required to package your Python projects, distribute them in distribution formats using steptools, upload them into the Python Package Index (PyPI) repository using twine, and finally installation using Python installers such as pip and conda.

  Pages: 1 2

  Tags: Distribution, Python

• The 6 components of Open-Source Data Science/ Machine Learning Ecosystem; Did Python declare victory over R? - Jun 6, 2018.
  
  We find 6 tools form the modern open source Data Science / Machine Learning ecosystem; examine whether Python declared victory over R; and review which tools are most associated with Deep Learning and Big Data.

  Tags: Anaconda, Apache Spark, Data Science, Keras, Machine Learning, Open Source, Poll, Python, R, RapidMiner, Scala, scikit-learn, TensorFlow

• ioModel Machine Learning Research Platform – Open Source - Jun 5, 2018.
  
  This article introduces ioModel, an open source research platform that ingests data and automatically generates descriptive statistics on that data.

  Tags: Data Preparation, GitHub, Machine Learning, Open Source, Postgres, Python

• The Keras 4 Step Workflow - Jun 4, 2018.
  
  In his book "Deep Learning with Python," Francois Chollet outlines a process for developing neural networks with Keras in 4 steps. Let's take a look at this process with a simple example.

  Tags: Keras, Neural Networks, Python, Workflow

• Overview of Dash Python Framework from Plotly for building dashboards - May 31, 2018.
  
  Introduction to Dash framework from Plotly, reactive framework for building dashboards in Python. Tech talk covers basics and more advanced topics like custom component and scaling.

  Tags: Dashboard, Data Analytics, Data Visualization, Plotly, Python

• NLP in Online Courses: an Overview - May 28, 2018.
  
  This article examines several Natural Language Processing (NLP) courses across a variety of online sources and programming languages.

  Tags: Coursera, edX, NLP, NLTK, Online Education, Python, Udemy

• Learn AI and Data Science rapidly based only on high school math – KDnuggets Offer - May 25, 2018.
  
  This 3-month program, created by Ajit Jaokar, who teaches at Oxford, is interactive and delivered by video. Coding examples are in Python. Places limited - check special KDnuggets rate.

  Tags: AI, Ajit Jaokar, Data Science Education, Mathematics, Online Education, Python

• KDnuggets™ News 18:n21, May 23: Python eats away at R; Top 2018 Analytics, Data Science, Machine Learning tools; 9 Must-have skills for a Data Scientist - May 23, 2018.
  
  Also How to Implement a YOLO (v3) Object Detector from Scratch in PyTorch; Frameworks for Approaching the Machine Learning Process.

  Tags: Data Science Platform, Data Science Skills, Poll, Python, PyTorch

• Python eats away at R: Top Software for Analytics, Data Science, Machine Learning in 2018: Trends and Analysis - May 22, 2018.
  
  Python continues to eat away at R, RapidMiner gains, SQL is steady, Tensorflow advances pulling along Keras, Hadoop drops, Data Science platforms consolidate, and more.

  Pages: 1 2

  Tags: Anaconda, Data Mining Software, Data Science Platform, Hadoop, Keras, Poll, Python, R, RapidMiner, SQL, TensorFlow, Trends

• Top Stories, May 14-20: Data Science vs Machine Learning vs Data Analytics vs Business Analytics; Implement a YOLO Object Detector from Scratch in PyTorch - May 21, 2018.
  
  Also: An Introduction to Deep Learning for Tabular Data; 9 Must-have skills you need to become a Data Scientist, updated; GANs in TensorFlow from the Command Line: Creating Your First GitHub Project; Complete Guide to Build ConvNet HTTP-Based Application

  Tags: Convolutional Neural Networks, Deep Learning, Image Recognition, Neural Networks, Python, PyTorch, TensorFlow, Top stories

• Kernel Machine Learning (KernelML) - Generalized Machine Learning Algorithm - May 18, 2018.
  
  This article introduces a pip Python package called KernelML, created to give analysts and data scientists a generalized machine learning algorithm for complex loss functions and non-linear coefficients.

  Tags: Clustering, Machine Learning, Python

• How to Implement a YOLO (v3) Object Detector from Scratch in PyTorch: Part 1 - May 17, 2018.
  
  The best way to go about learning object detection is to implement the algorithms by yourself, from scratch. This is exactly what we'll do in this tutorial.

  Tags: Computer Vision, Image Recognition, Neural Networks, Python, PyTorch

• GANs in TensorFlow from the Command Line: Creating Your First GitHub Project - May 16, 2018.
  
  In this article I will present the steps to create your first GitHub Project. I will use as an example Generative Adversarial Networks.

  Tags: Generative Adversarial Network, GitHub, Neural Networks, Python, Rubens Zimbres, TensorFlow

• KDnuggets™ News 18:n20, May 16: PyTorch Tensor Basics; Data Science in Finance; Executive Guide to Data Science - May 16, 2018.
  
  PyTorch Tensor Basics; Top 7 Data Science Use Cases in Finance; The Executive Guide to Data Science and Machine Learning; Data Augmentation: How to use Deep Learning when you have Limited Data

  Tags: Computer Vision, Data Science, Deep Learning, Finance, Neural Networks, Python, PyTorch, Tensor, Wikidata

• Complete Guide to Build ConvNet HTTP-Based Application using TensorFlow and Flask RESTful Python API - May 15, 2018.
  
  In this tutorial, a CNN is to be built, and trained and tested against the CIFAR10 dataset. To make the model remotely accessible, a Flask Web application is created using Python to receive an uploaded image and return its classification label using HTTP.

  Pages: 1 2

  Tags: API, Convolutional Neural Networks, Flask, Neural Networks, Python, RESTful API, TensorFlow

• Simple Derivatives with PyTorch - May 14, 2018.
  
  PyTorch includes an automatic differentiation package, autograd, which does the heavy lifting for finding derivatives. This post explores simple derivatives using autograd, outside of neural networks.

  Tags: Python, PyTorch

• PyTorch Tensor Basics - May 11, 2018.
  
  This is an introduction to PyTorch's Tensor class, which is reasonably analogous to Numpy's ndarray, and which forms the basis for building neural networks in PyTorch.

  Tags: GPU, Python, PyTorch, Tensor

• Unleash a faster Python on Your Data. - May 10, 2018.
  
  Get real performance results and download the free Intel(r) Distribution for Python that includes everything you need for blazing-fast computing, analytics, machine learning, and more.

  Tags: free download, Intel, numpy, Python

• 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.

  Tags: 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.

  Tags: 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.

  Tags: Azure ML, Data Science, Machine Learning, Python, Udemy

• WTF is a Tensor?!? - May 7, 2018.
  
  A tensor is a container which can house data in N dimensions, along with its linear operations, though there is nuance in what tensors technically are and what we refer to as tensors in practice.

  Tags: numpy, Python, Tensor

• 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.

  Tags: 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.

  Tags: Data Science, 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.

  Tags: 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.

  Tags: 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

  Tags: 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

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: 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!

  Tags: 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.

  Tags: 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.

  Tags: 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

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: 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!

  Tags: 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.

  Tags: 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

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: 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?

  Tags: Classification, Image Recognition, 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.

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: CoLaboratory, Google, 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

  Tags: 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.

  Tags: 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.

  Tags: 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

  Tags: 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.

  Tags: 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.

  Tags: 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

  Tags: 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

  Tags: 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.

  Tags: 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.

  Tags: 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

  Tags: CoLaboratory, Deep Learning, Google, 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)

  Tags: Algorithms, CoLaboratory, Data Science, Ensemble methods, fast.ai, Feature Engineering, 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.

  Tags: CoLaboratory, Google, 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

  Tags: Decision Trees, Ensemble methods, Machine Learning, Python, Random Forests, 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!

  Tags: 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

  Tags: 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?

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: 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

  Tags: 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).

  Tags: Automated Machine Learning, Genetic, 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.

  Tags: 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.

  Tags: Machine Learning, 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.

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: 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

  Tags: 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.

  Tags: 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

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: 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

  Tags: 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?

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: 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!

  Tags: 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.

  Tags: 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

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: 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.

  Tags: Bootcamp, Data Science, Data Visualization, Machine Learning, NLP, Python, R, Switzerland, Zurich