Decoding the Black Box: An Important Introduction to Interpretable Machine Learning Models in Python

Analytics Vidhya

Overview Interpretable machine learning is a critical concept every data scientist should be aware of How can you build interpretable machine learning models?

The Ultimate List of Popular Machine Learning Use Cases in our Day-to-Day Life

Analytics Vidhya

Overview We are the in middle of a golden age of machine learning applications Here’s a comprehensive list of popular and common machine learning.

Top 7 Machine Learning Github Repositories for Data Scientists

Analytics Vidhya

Introduction If I had to pick one platform that has single-handedly kept me up-to-date with the latest developments in data science and machine learning. The post Top 7 Machine Learning Github Repositories for Data Scientists appeared first on Analytics Vidhya.

A Detailed Guide to 7 Loss Functions for Machine Learning Algorithms with Python Code

Analytics Vidhya

And how do they work in machine learning algorithms? The post A Detailed Guide to 7 Loss Functions for Machine Learning Algorithms with Python Code appeared first on Analytics Vidhya. Overview What are loss functions?

Using a Machine Learning Data Catalog to Reboot Data Governance

Speaker: David Loshin, President, Knowledge Integrity, Inc, and Sharon Graves, Enterprise Data - BI Tools Evangelist, GoDaddy

Here are 7 Data Science Projects on GitHub to Showcase your Machine Learning Skills!

Analytics Vidhya

The post Here are 7 Data Science Projects on GitHub to Showcase your Machine Learning Skills! Overview Working on Data Science projects is a great way to stand out from the competition Check out these 7 data science projects on.

6 Powerful Open Source Machine Learning GitHub Repositories for Data Scientists

Analytics Vidhya

Overview Check out the top 6 machine learning GitHub repositories created in June There’s a heavy focus on NLP again, with XLNet outperforming Google’s.

Build a Machine Learning Model in your Browser using TensorFlow.js and Python

Analytics Vidhya

Overview TensorFlow.js (deeplearn.js) enables us to build machine learning and deep learning models right in our browser without needing any complex installation steps There. The post Build a Machine Learning Model in your Browser using TensorFlow.js

Heroes of Machine Learning – Top Experts and Researchers you should follow

Analytics Vidhya

Overview The path to democratizing machine learning has been blazed by experts and researchers determined to make the world a better place We celebrate. The post Heroes of Machine Learning – Top Experts and Researchers you should follow appeared first on Analytics Vidhya. Career Machine Learning deep learning researchers heroes of deep learning heroes of machine learning machine learning experts machine learning researchers top ML experts

Cartoon: Unsupervised Machine Learning?

KDnuggets

New KDnuggets Cartoon looks at one of the hottest directions in Machine Learning and asks can Machine Learning be too unsupervised? 2019 Sep Opinions Cartoon Humor Machine Learning Unsupervised Learning

Common Machine Learning Obstacles

KDnuggets

2019 Sep Opinions Cross-validation Decision Trees Logistic Regression Machine Learning MathWorks Overfitting SVMIn this blog, Seth DeLand of MathWorks discusses two of the most common obstacles relate to choosing the right classification model and eliminating data overfitting.

Want to Build Machine Learning Pipelines? A Quick Introduction using PySpark

Analytics Vidhya

Overview Here’s a quick introduction to building machine learning pipelines using PySpark The ability to build these machine learning pipelines is a must-have skill. The post Want to Build Machine Learning Pipelines?

21 Must-Know Open Source Tools for Machine Learning you Probably Aren’t Using (but should!)

Analytics Vidhya

Overview Presenting 21 open source tools for Machine Learning you might not have come across Each open-source tool here adds a different aspect to. The post 21 Must-Know Open Source Tools for Machine Learning you Probably Aren’t Using (but should!) Big data Machine Learning Python Big Data tools data science data science tools machine learning Machine Learning tools python python tools reinforcement learning tools

Training a Machine Learning Engineer

KDnuggets

There is no clear outline on how to study Machine Learning/Deep Learning due to which many individuals apply all the possible algorithms that they have heard of and hope that one of implemented algorithms work for their problem in hand.

Top 5 Machine Learning GitHub Repositories and Reddit Discussions from March 2019

Analytics Vidhya

Introduction GitHub repositories and Reddit discussions – both platforms have played a key role in my machine learning journey. The post Top 5 Machine Learning GitHub Repositories and Reddit Discussions from March 2019 appeared first on Analytics Vidhya.

Mathematics behind Machine Learning – The Core Concepts you Need to Know

Analytics Vidhya

Overview Here’s an intuitive and beginner friendly guide to the mathematics behind machine learning Learn the various math concepts required for machine learning, including. The post Mathematics behind Machine Learning – The Core Concepts you Need to Know appeared first on Analytics Vidhya. Machine Learning

Deep automation in machine learning

O'Reilly on Data

In a previous post , we talked about applications of machine learning (ML) to software development, which included a tour through sample tools in data science and for managing data infrastructure. But this process only applies to a single machine learning platform: Spark.

Managing risk in machine learning

O'Reilly on Data

As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations. We recently conducted a survey which garnered more than 11,000 respondents—our main goal was to ascertain how enterprises were using machine learning.

Risk 267

11 Important Model Evaluation Metrics for Machine Learning Everyone should know

Analytics Vidhya

Overview Evaluating a model is a core part of building an effective machine learning model There are several evaluation metrics, like confusion matrix, cross-validation, The post 11 Important Model Evaluation Metrics for Machine Learning Everyone should know appeared first on Analytics Vidhya.

Data Mapping Using Machine Learning

KDnuggets

2019 Sep Opinions Data Cleaning Data Preparation Machine LearningData mapping is a way to organize various bits of data into a manageable and easy-to-understand system.

Sustaining machine learning in the enterprise

O'Reilly on Data

Drawing insights from recent surveys, Ben Lorica analyzes important trends in machine learning. Continue reading Sustaining machine learning in the enterprise

Understanding Cancer using Machine Learning

KDnuggets

Use of Machine Learning (ML) in Medicine is becoming more and more important. 2019 Aug Tutorials, Overviews Cancer Detection Healthcare Machine Learning MedicalOne application example can be Cancer Detection and Analysis.

Deployed your Machine Learning Model? Here’s What you Need to Know About Post-Production Monitoring

Analytics Vidhya

Overview What are the next steps after you’ve deployed your machine learning model? Post-deployment monitoring is a crucial step in any machine learning project. The post Deployed your Machine Learning Model? Data Science deployment machine learning model deployment model monitoringHere’s What you Need to Know About Post-Production Monitoring appeared first on Analytics Vidhya.

A Unique Method for Machine Learning Interpretability: Game Theory & Shapley Values!

Analytics Vidhya

Overview Learn how to use Shapley values in game theory for machine learning interpretability It’s a unique and different perspective to interpret black-box machine. The post A Unique Method for Machine Learning Interpretability: Game Theory & Shapley Values! Machine Learning Python Technique Game Theory machine learning interpretability python shapley value

Choosing a Machine Learning Model

KDnuggets

Selecting the perfect machine learning model is part art and part science. Learn how to review multiple models and pick the best in both competitive and real-world applications. 2019 Oct Opinions Interpretability Kaggle Machine Learning

Statistical Modelling vs Machine Learning

KDnuggets

At times it may seem Machine Learning can be done these days without a sound statistical background but those people are not really understanding the different nuances. 2019 Aug Opinions Uncategorized Advice Data Science Machine Learning Statistics

Machine learning on encrypted data

O'Reilly on Data

The O’Reilly Data Show Podcast: Alon Kaufman on the interplay between machine learning, encryption, and security. As I noted, the main motivation for improving data liquidity is the growing importance of machine learning.

Scikit-Learn vs mlr for Machine Learning

KDnuggets

How does the scikit-learn machine learning library for Python compare to the mlr package for R? Following along with a machine learning workflow through each approach, and see if you can gain a competitive advantage by knowing both frameworks.

Announcing DataHack Summit 2019 – The Biggest Artificial Intelligence and Machine Learning Conference Yet

Analytics Vidhya

The post Announcing DataHack Summit 2019 – The Biggest Artificial Intelligence and Machine Learning Conference Yet appeared first on Analytics Vidhya. Analytics Vidhya AI Artificial Intelligence artificial intelligence conference datahack summit DataHack Summit 2019 deep learning DHS 2019 machine learning machine learning conference super AI

Python Libraries for Interpretable Machine Learning

KDnuggets

In the following post, I am going to give a brief guide to four of the most established packages for interpreting and explaining machine learning models. 2019 Sep Tutorials, Overviews Bias Interpretability LIME Machine Learning Python SHAP

Big Data, Machine Learning and Alteryx Inspires 2019

David Menninger's Analyst Perspectives

This year's conference focused on Alteryx's evolution from data preparation to AI and machine learning, and both were front and center. Big Data Data Science alteryx Machine Learning Data Integration Data Management Alteryx Inspire

How I Got Better at Machine Learning

KDnuggets

Check out this author's collection of tips and tricks that I learned over the years to get better at Machine Learning. 2019 Nov Opinions Advice Machine Learning Tips

DataHack Radio #21: Detecting Fake News using Machine Learning with Mike Tamir, Ph.D.

Analytics Vidhya

The post DataHack Radio #21: Detecting Fake News using Machine Learning with Mike Tamir, Ph.D. Podcast data science podcast DataHack Radio DataHack Radio Podcast machine learning machine learning podcast NLPIntroduction Fake news is one of the biggest scourges in our digitally connected world. That is no exaggeration. It is no longer limited to. appeared first on Analytics Vidhya.

Automated Machine Learning: Just How Much?

KDnuggets

This is an interview between Rosaria Silipo and data scientists Paolo Tamagnini, Simon Schmid and Christian Dietz, asking a few questions on the topic of automated machine learning from their point of view, and some interesting examples of its practical use.

A Doomed Marriage of Machine Learning and Agile

KDnuggets

Sebastian Thrun, the founder of Udacity, ruined my machine learning project and wedding. 2019 Nov Opinions Agile Machine Learning Udacity

Knowing Your Neighbours: Machine Learning on Graphs

KDnuggets

Graph Machine Learning uses the network structure of the underlying data to improve predictive outcomes. Learn how to use this modern machine learning method to solve challenges with connected data.

How Machine Learning Will Impact Climate Research

DataFloq

Machine learning and artificial intelligence may just be our big leap. The slow switch to renewable energy has already seen success all over the world, but there's more that machine learning can teach us about power. Climate change is only getting worse as time goes on.

Trends in data, machine learning, and AI

O'Reilly on Data

For the end-of-year holiday episode of the Data Show , I turned the tables on Data Show host Ben Lorica to talk about trends in big data, machine learning, and AI, and what to look for in 2019. Continue reading Trends in data, machine learning, and AI

Meta-Learning For Better Machine Learning

Rocket-Powered Data Science

The above example (clustering) is taken from unsupervised machine learning (where there are no labels on the training data). There are also examples of cold start in supervised machine learning (where you do have class labels on the training data).

How machine learning impacts information security

O'Reilly on Data

They list important changes to the information landscape and offer suggestions on how to alleviate some of the new risks introduced by the rise of machine learning and AI. Continue reading How machine learning impacts information security