Tag: Python (555)

• Data Augmentation For Bounding Boxes: Rethinking image transforms for object detection - Sep 19, 2018.
  
  Data Augmentation is one way to battle this shortage of data, by artificially augmenting our dataset. In fact, the technique has proven to be so successful that it's become a staple of deep learning systems.

  Pages: 1 2

  Tags: Deep Learning, Image Recognition, Neural Networks, Object Detection, Python

• Iterative Initial Centroid Search via Sampling for k-Means Clustering - Sep 12, 2018.
  
  Thinking about ways to find a better set of initial centroid positions is a valid approach to optimizing the k-means clustering process. This post outlines just such an approach.

  Tags: Clustering, K-means, Python, Sampling, scikit-learn

• Machine Learning for Text Classification Using SpaCy in Python - Sep 11, 2018.
  
  In this post, we will demonstrate how text classification can be implemented using spaCy without having any deep learning experience.

  Tags: NLP, Python, Text Analytics, Text Classification, Text Mining

• Training with Keras-MXNet on Amazon SageMaker - Sep 10, 2018.
  
  In this post, you will learn how to train Keras-MXNet jobs on Amazon SageMaker. I’ll show you how to build custom Docker containers for CPU and GPU training, configure multi-GPU training, pass parameters to a Keras script, and save the trained models in Keras and MXNet formats.

  Pages: 1 2

  Tags: Docker, Keras, MXNet, Neural Networks, Python

• Journey to Machine Learning – 100 Days of ML Code - Sep 7, 2018.
  
  A personal account from Machine Learning enthusiast Avik Jain on his experiences of #100DaysOfMLCode, a challenge that encourages beginners to code and study machine learning for at least an hour, every day for 100 days.

  Tags: GitHub, K-nearest neighbors, Machine Learning, Python, Support Vector Machines

• Ultimate Guide to Getting Started with TensorFlow - Sep 6, 2018.
  
  Including video and written tutorials, beginner code examples, useful tricks, helpful communities, books, jobs and more - this is the ultimate guide to getting started with TensorFlow.

  Tags: Deep Learning, Dropout, Python, TensorFlow

• KDnuggets™ News 18:n33, Sep 5: Practical Topic Modeling with Python; Classifying AI Technologies; Data Science Project Inspiration - Sep 5, 2018.
  
  Also: An End-to-End Project on Time Series Analysis and Forecasting with Python; Financial Data Analysis - Data Processing 1: Loan Eligibility Prediction; OLAP queries in SQL: A Refresher; Word Vectors in Natural Language Processing: Global Vectors (GloVe)

  Tags: AI, Data Science, Finance, OLAP, Python, SQL, Time Series, Topic Modeling, Word Embeddings

• Financial Data Analysis – Data Processing 1: Loan Eligibility Prediction - Sep 4, 2018.
  
  In this first part I show how to clean and remove unnecessary features. Data processing is very time-consuming, but better data would produce a better model.

  Tags: Data Preprocessing, Data Processing, Finance, Python

• An End-to-End Project on Time Series Analysis and Forecasting with Python - Sep 3, 2018.
  
  Time series are widely used for non-stationary data, like economic, weather, stock price, and retail sales in this post. We will demonstrate different approaches for forecasting retail sales time series.

  Tags: Forecasting, Python, Time Series, Trend Detection

• Optimus v2: Agile Data Science Workflows Made Easy - Aug 30, 2018.
  
  Looking for a library to skyrocket your productivity as Data Scientist? Check this out!

  Tags: Apache Spark, Machine Learning, Pandas, Python

• Top KDnuggets tweets, Aug 22-28: AI Knowledge Map: How To Classify AI Technologies; 100 Days of #MachineLearning Coding with #Python - Aug 29, 2018.
  
  Also 25 fun questions for a machine learning interview; Data Visualization Cheat Sheet

  Tags: AI, Data Visualization, Interview questions, Machine Learning, Python, Top tweets

• Deploying scikit-learn Models at Scale - Aug 29, 2018.
  
  Find out how to serve your scikit-learn model in an auto-scaling, serverless environment! Today, we’ll take a trained scikit-learn model and deploy it on Cloud ML Engine.

  Tags: Cloud, Google, Google Cloud, Machine Learning, Python, scikit-learn

• Multi-Class Text Classification with Scikit-Learn - Aug 27, 2018.
  
  The vast majority of text classification articles and tutorials on the internet are binary text classification such as email spam filtering and sentiment analysis. Real world problem are much more complicated than that.

  Tags: NLP, Python, scikit-learn, Text Classification, Text Mining

• Analyze, engineer, design: Do it all with Dash - Aug 24, 2018.
  
  Open-source Dash lets you wrap a GUI around that analytical code, without leaving the familiarity of Python. Explore your data with rich, interactive drop-down menus, sliders, and other components, all in the web browser.

  Tags: Dash, Data Visualization, Open Source, Plotly, Python

• 9 Things You Should Know About TensorFlow - Aug 22, 2018.
  
  A summary of the key points from the Google Cloud Next in San Francisco, "What’s New with TensorFlow?", including neural networks, TensorFlow Lite, data pipelines and more.

  Tags: Deep Learning, Google, Keras, Machine Learning, Python, TensorFlow

• Kinetica: Software Engineer (Python) [Arlington, VA] - Aug 21, 2018.
  
  Work closely with the Product Owner to build out the product in Python and integrate all other parts (TensorFlow, Kubernetes, and our GPU-powered DB) using Python bindings to build and deliver an overall product (a REST API).

  Tags: Arlington, Database, GPU, Kinetica, Python, Software Engineer, VA

• Basic Statistics in Python: Probability - Aug 21, 2018.
  
  At the most basic level, probability seeks to answer the question, "What is the chance of an event happening?" To calculate the chance of an event happening, we also need to consider all the other events that can occur.

  Tags: Probability, Python, Statistics

• Why Automated Feature Engineering Will Change the Way You Do Machine Learning - Aug 20, 2018.
  
  Automated feature engineering will save you time, build better predictive models, create meaningful features, and prevent data leakage.

  Tags: Automated Machine Learning, Feature Engineering, Machine Learning, Python

• Introduction to Fraud Detection Systems - Aug 17, 2018.
  
  Using the Python gradient boosting library LightGBM, this article introduces fraud detection systems, with code samples included to help you get started.

  Tags: Fraud Detection, Gradient Boosting, Python

• Auto-Keras, or How You can Create a Deep Learning Model in 4 Lines of Code - Aug 17, 2018.
  
  Auto-Keras is an open source software library for automated machine learning. Auto-Keras provides functions to automatically search for architecture and hyperparameters of deep learning models.

  Tags: Automated Machine Learning, Keras, Neural Networks, Python

• Machine Learning with TensorFlow - Aug 16, 2018.
  
  In this on-demand webinar, you’ll get a general introduction to working with Tensorflow and its surrounding ecosystem, general problem classes, where you can get big acceleration, and why you should be running on a CPU.

  Tags: ActiveState, Intel, Machine Learning, Python, TensorFlow

• A Crash Course in MXNet Tensor Basics & Simple Automatic Differentiation - Aug 16, 2018.
  
  This is an overview of some basic functionality of the MXNet ndarray package for creating tensor-like objects, and using the autograd package for performing automatic differentiation.

  Tags: GPU, MXNet, Python, Tensor

• Top KDnuggets tweets, Aug 1-14: Basic Statistics in Python; Essential Command Line Tools for Data Scientists - Aug 15, 2018.
  
  Basic Statistics in Python: Descriptive Statistics; Top 12 Essential Command Line Tools for Data Scientists; WTF is a Tensor?!?; How GOAT Taught a Machine to Love Sneakers;

  Tags: Python, Statistics, Tensor, Top tweets

• An Introduction to t-SNE with Python Example - Aug 15, 2018.
  
  In this post we’ll give an introduction to the exploratory and visualization t-SNE algorithm. t-SNE is a powerful dimension reduction and visualization technique used on high dimensional data.

  Tags: Clustering, Data Visualization, PCA, Python, t-SNE

• KDnuggets™ News 18:n31, Aug 15: Top 10 roles in AI and data science; Github Data Science Spotlight: Python tools for Machine Learning - Aug 15, 2018.
  
  Also: A Practitioner Guide to NLP; Reinforcement Learning: The Business Use Case; Data Scientist guide for getting started with Docker

  Tags: Career, Data Science, Docker, GitHub, Jobs, Python

• Setting up your AI Dev Environment in 5 Minutes - Aug 13, 2018.
  
  Whether you're a novice data science enthusiast setting up TensorFlow for the first time, or a seasoned AI engineer working with terabytes of data, getting your libraries, packages, and frameworks installed is always a struggle. Learn how datmo, an open source python package, helps you get started in minutes.

  Tags: AI, datmo, Development, Docker, Machine Learning, Python, TensorFlow

• Optimization 101 for Data Scientists - Aug 8, 2018.
  
  We show how to use optimization strategies to make the best possible decision.

  Tags: Football, Julia, Optimization, Python, R, Sports

• GitHub Python Data Science Spotlight: AutoML, NLP, Visualization, ML Workflows - Aug 8, 2018.
  
  This post includes a wide spectrum of data science projects, all of which are open source and are present on GitHub repositories.

  Tags: Automated Machine Learning, Data Science, Data Visualization, GitHub, Keras, Machine Learning, NLP, Python, Workflow

• KDnuggets™ News 18:n30, Aug 8: Iconic Data Visualisation; Data Scientist Interviews Demystified; Simple Statistics in Python - Aug 8, 2018.
  
  Also: Selecting the Best Machine Learning Algorithm for Your Regression Problem; From Data to Viz: how to select the the right chart for your data; Only Numpy: Implementing GANs and Adam Optimizer using Numpy; Programming Best Practices for Data Science

  Tags: Data Science, Data Visualization, Generative Adversarial Network, Interview, Machine Learning, numpy, Python, Regression, Statistics

• Programming Best Practices For Data Science - Aug 7, 2018.
  
  In this post, I'll go over the two mindsets most people switch between when doing programming work specifically for data science: the prototype mindset and the production mindset.

  Tags: Best Practices, Data Science, Pandas, Programming, Python

• Only Numpy: Implementing GANs and Adam Optimizer using Numpy - Aug 6, 2018.
  
  This post is an implementation of GANs and the Adam optimizer using only Python and Numpy, with minimal focus on the underlying maths involved.

  Tags: Generative Adversarial Network, Neural Networks, numpy, Optimization, Python

• WTF is TF-IDF? - Aug 2, 2018.
  
  Relevant words are not necessarily the most frequent words since stopwords like “the”, “of” or “a” tend to occur very often in many documents.

  Tags: Information Retrieval, Python, Text Analytics, Text Mining

• Basic Statistics in Python: Descriptive Statistics - Aug 1, 2018.
  
  This article covers defining statistics, descriptive statistics, measures of central tendency, and measures of spread. This article assumes no prior knowledge of statistics, but does require at least a general knowledge of Python.

  Tags: Descriptive Analytics, Python, Statistics

• Intuitive Ensemble Learning Guide with Gradient Boosting - Jul 30, 2018.
  
  This tutorial discusses the importance of ensemble learning with gradient boosting as a study case.

  Tags: Ensemble methods, Gradient Boosting, Python

• Remote Data Science: How to Send R and Python Execution to SQL Server from Jupyter Notebooks - Jul 27, 2018.
  
  Did you know that you can execute R and Python code remotely in SQL Server from Jupyter Notebooks or any IDE? Machine Learning Services in SQL Server eliminates the need to move data around.

  Tags: Jupyter, Machine Learning, Microsoft, Python, R, SQL, SQL Server

• KDnuggets™ News 18:n28, Jul 25: Best (and Free) Resources to Understand Deep Learning; Why Germany did not beat Brazil in the final – Data Science lessons from the World Cup - Jul 25, 2018.
  
  Also 5 Quick and Easy Data Visualizations in Python with Code; Happy 25th Birthday, KDnuggets!

  Tags: About KDnuggets, Data Visualization, Deep Learning, Python, World Cup

• Genetic Algorithm Implementation in Python - Jul 24, 2018.
  
  This tutorial will implement the genetic algorithm optimization technique in Python based on a simple example in which we are trying to maximize the output of an equation.

  Tags: Algorithms, Genetic, Python

• Cookiecutter Data Science: How to Organize Your Data Science Project - Jul 24, 2018.
  
  A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.

  Tags: Data Science, Programming, Python

• Improve Data Science Productivity with Anaconda Enterprise - Jul 23, 2018.
  
  Anaconda Enterprise is the only product on the market that empowers your data science team to go from laptop to cluster to production with full reproducibility and governance.

  Tags: Anaconda, Data Science, Enterprise, Python

• Comparison of Top 6 Python NLP Libraries - Jul 23, 2018.
  
  Today, we want to outline and compare the most popular and helpful natural language processing libraries, based on our experience.

  Tags: NLP, Python

• Receiver Operating Characteristic Curves Demystified (in Python) - Jul 20, 2018.
  
  In this blog, I will reveal, step by step, how to plot an ROC curve using Python. After that, I will explain the characteristics of a basic ROC curve.

  Tags: Machine Learning, Metrics, Python

• 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 Processing in Python, 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, 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, Object Detection, 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, Object Detection, Python, PyTorch, YOLO

• 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, Dropout, 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, 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.

  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