Oct2019 Nov
All (35) | Courses, Education (1) | Meetings (1) | News (2) | Opinions (5) | Top Stories, Tweets (4) | Tutorials, Overviews (19) | Webcasts & Webinars (3)
- How to Speed up Pandas by 4x with one line of code
- Nov 12, 2019.
While Pandas is the library for data processing in Python, it isn't really built for speed. Learn more about the new library, Modin, developed to distribute Pandas' computation to speedup your data prep.
- Understanding NLP and Topic Modeling Part 1
- Nov 12, 2019.
In this post, we seek to understand why topic modeling is important and how it helps us as data scientists.
- MLOps for production-level machine learning [Nov 14 Webinar]
- Nov 12, 2019.
This live webinar, Nov 14 @ 12pm EST, on MLOps for production-level machine learning, will detail MLOps, a compound of “machine learning” and “operations”, a practice for collaboration and communication between data scientists and operations professionals to help manage the production machine learning lifecycle. Register now.
- Research Guide for Depth Estimation with Deep Learning
- Nov 12, 2019.
In this guide, we’ll look at papers aimed at solving the problems of depth estimation using deep learning.
- How to Extract Google Maps Coordinates
- Nov 11, 2019.
In this article, I will show you how to quickly extract Google Maps coordinates with a simple and easy method.
- The Complete Data Science LinkedIn Profile Guide
- Nov 11, 2019.
With so many Data Scientists showing up on LinkedIn, it's time to make sure your profile is top-notch because your talent is still highly sought after. Recruitment specialists want to find you fast, and this guide will help you create the best profile to feature your expertise.
- Top Stories, Nov 4-10: 10 Free Must-read Books on AI
- Nov 11, 2019.
Also: Understanding Boxplots; Probability Learning: Maximum Likelihood; Designing Your Neural Networks; Facebook Has Been Quietly Open Sourcing Some Amazing Deep Learning Capabilities for PyTorch; 5 Statistical Traps Data Scientists Should Avoid
- How Data Analytics Can Assist in Fraud Detection
- Nov 11, 2019.
A primary advantage of data analytics tools is that they can handle massive quantities of information at once. These solutions typically learn what's normal within a collection of information and how to spot anomalies.
- Facebook Adds This New Framework to It’s Reinforcement Learning Arsenal
- Nov 11, 2019.
ReAgent is a new framework that streamlines the implementation of reasoning systems.
- Top October Stories: How to Become a (Good) Data Scientist; Everything a Data Scientist Should Know About Data Management; The Last SQL Guide for Data Analysis
- Nov 8, 2019.
Also A European Approach to Master's Degrees in Data Science; How YouTube is Recommending Your Next Video
- What is Data Science?
- Nov 8, 2019.
Data Science is pitched as a modern and exciting job offering high satisfaction. Does its reality really live up to the hype? Here, we show what it's really like to work as a Data Scientist.
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Understanding Boxplots
- Nov 8, 2019.
A boxplot. It can tell you about your outliers and what their values are. It can also tell you if your data is symmetrical, how tightly your data is grouped, and if and how your data is skewed. - Orchestrating Dynamic Reports in Python and R with Rmd Files
- Nov 8, 2019.
Do you want to extract csv files with Python and visualize them in R? How does preparing everything in R and make conclusions with Python sound? Both are possible if you know the right libraries and techniques. Here, we’ll walk through a use-case using both languages in one analysis
- 3 Reasons to attend Data Natives, 25-26 November, Berlin
- Nov 8, 2019.
Data Natives is an outstanding conference that lets you meet many talented Data Scientists and Data Professionals. Find your dream company or your dream employee and level up for 2020. Use code DN19_KDNuggets_50 to save.
- Monitoring Models at Scale
- Nov 7, 2019.
Catch this Domino webinar on monitoring models at scale, Dec 11 @ 10am PT, covering detecting changes in pattern of real-world data your models are seeing in production, tracking how model accuracy and other quality metrics are changing over time, and getting alerted when health checks fail so that resolution workflows can be triggered.
- Data Cleaning and Preprocessing for Beginners
- Nov 7, 2019.
Careful preprocessing of data for your machine learning project is crucial. This overview describes the process of data cleaning and dealing with noise and missing data.
- Set Operations Applied to Pandas DataFrames
- Nov 7, 2019.
In this tutorial, we show how to apply mathematical set operations (union, intersection, and difference) to Pandas DataFrames with the goal of easing the task of comparing the rows of two datasets.
- How to Create a Vocabulary for NLP Tasks in Python
- Nov 7, 2019.
This post will walkthrough a Python implementation of a vocabulary class for storing processed text data and related metadata in a manner useful for subsequently performing NLP tasks.
- Top KDnuggets tweets, Oct 30 – Nov 05: Everything a Data Scientist Should Know About Data Management
- Nov 6, 2019.
Which Data Science Skills are core and which are hot/emerging ones?; The 4 Quadrants of Data Science Skills and 7 Principles for Creating a Viral DataViz; Microsoft open sources #SandDance, a visual data exploration tool.
- Meet Neebo: The Virtual Analytics Hub
- Nov 6, 2019.
Neebo is a SaaS solution that enables analytics teams to connect to, find, combine and collaborate on trusted data assets in hybrid cloud landscapes, and provides a unified access point where they can more effectively leverage all their analytics assets and knowledge. In this blog, we will highlight some of the features of Neebo and how they can completely transform the way analytics teams operate.
- An Eight-Step Checklist for An Analytics Project
- Nov 6, 2019.
Follow these eight headings of an audit sheet that business analysts should address before submitting the results of their analytics project. One recommended approach is to rewrite each step as a question, answer it, and then attach it to your project.
- Research Guide: Advanced Loss Functions for Machine Learning Models
- Nov 6, 2019.
This guide explores research centered on a variety of advanced loss functions for machine learning models.
- The Last Defense Against Another AI Winter
- Nov 6, 2019.
My short answer is this: Yes, another AI Winter will be here if you don’t deploy more ML solutions. You and your Data Science teams are the last line of defense against the AI Winter. You need to solve five key challenges to keep the momentum up.
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10 Free Must-read Books on AI
- Nov 5, 2019.
Artificial Intelligence continues to fill the media headlines while scientists and engineers rapidly expand its capabilities and applications. With such explosive growth in the field, there is a great deal to learn. Dive into these 10 free books that are must-reads to support your AI study and work. - Probability Learning: Maximum Likelihood
- Nov 5, 2019.
The maths behind Bayes will be better understood if we first cover the theory and maths underlying another fundamental method of probabilistic machine learning: Maximum Likelihood. This post will be dedicated to explaining it.
- How to Become a Successful Healthcare Data Analyst
- Nov 5, 2019.
Are you interested in starting your career in the data analysis domain? Read this informative blog on how to get your career off the ground.
- Top Stories, Oct 28 – Nov 3: 5 Statistical Traps Data Scientists Should Avoid; Top Machine Learning Software Tools for Developers
- Nov 4, 2019.
Also: Why is Machine Learning Deployment Hard?; Data Sources 101; 5 Statistical Traps Data Scientists Should Avoid; Everything a Data Scientist Should Know About Data Management; How to Become a (Good) Data Scientist — Beginner Guide
- Practical Computer Vision Course with Real-Life Cases, Nov 18, Washington, DC
- Nov 4, 2019.
This course, Practical Computer Vision Course with Real-Life Cases, Nov 18 in Washington, DC, will move you on the next step, providing you with practical means of solving business-specific tasks.Reserve your seat now.
- Designing Your Neural Networks
- Nov 4, 2019.
Check out this step-by-step walk through of some of the more confusing aspects of neural nets to guide you to making smart decisions about your neural network architecture.
- Customer Segmentation Using K Means Clustering
- Nov 4, 2019.
Customer Segmentation can be a powerful means to identify unsatisfied customer needs. This technique can be used by companies to outperform the competition by developing uniquely appealing products and services.
- Facebook Has Been Quietly Open Sourcing Some Amazing Deep Learning Capabilities for PyTorch
- Nov 4, 2019.
The new release of PyTorch includes some impressive open source projects for deep learning researchers and developers.
- Top Machine Learning Software Tools for Developers
- Nov 1, 2019.
As a developer who is excited about leveraging machine learning for faster and more effective development, these software tools are worth trying out.
- Build an Artificial Neural Network From Scratch: Part 1
- Nov 1, 2019.
This article focused on building an Artificial Neural Network using the Numpy Python library.
- MLOps for production-level machine learning
- Nov 1, 2019.
This live webinar, Nov 14 @ 12pm EST, on MLOps for production-level machine learning, will detail MLOps, a compound of “machine learning” and “operations”, a practice for collaboration and communication between data scientists and operations professionals to help manage the production machine learning lifecycle. Register now.
- What is Machine Learning on Code?
- Nov 1, 2019.
Not only can MLonCode help companies streamline their codebase and software delivery processes, but it also helps organizations better understand and manage their engineering talents.
