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?

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.

7 Innovative Machine Learning GitHub Projects you Should Try Out in Python

Analytics Vidhya

Overview Looking for machine learning projects to do right now? Here are 7 wide-ranging GitHub projects to try out These projects cover multiple machine. The post 7 Innovative Machine Learning GitHub Projects you Should Try Out in Python appeared first on Analytics Vidhya.

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.

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.

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?

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

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

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

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.

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.

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

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

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.

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

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.

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.

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 263

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.

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

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

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.

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.

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.

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

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.

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

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.

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.

Machine learning: Changing the Beauty Industry

DataFloq

So, maybe, it is time for machine learning to transform beauty salons where traditional biology and pharmacy fail? Several years ago a friend of mine, who was a biologist, was talking about their weird experiments.

Ensemble Methods for Machine Learning: AdaBoost

KDnuggets

2019 Sep Tutorials, Overviews Adaboost Ensemble Methods Machine Learning PythonIt turned out that, if we ask the weak algorithm to create a whole bunch of classifiers (all weak for definition), and then combine them all, what may figure out is a stronger classifier.

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).

Becoming a machine learning company means investing in foundational technologies

O'Reilly on Data

Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. A famous example is Google’s machine translation system, which shifted from “stats focused” approaches to TensorFlow.

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

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

Webinar: Build auto-adaptive machine learning models with Kubernetes

KDnuggets

This live webinar, Oct 2 2019, will instruct data scientists and machine learning engineers how to build manage and deploy auto-adaptive machine learning models in production. Kubernetes Machine Learning

Applications of data science and machine learning in financial services

O'Reilly on Data

Chong has extensive experience using analytics and machine learning in financial services, and he has experience building data science teams in the U.S. Continue reading Applications of data science and machine learning in financial services

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.

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

An Easy Introduction to Machine Learning Recommender Systems

KDnuggets

Recommender systems are an important class of machine learning algorithms that offer "relevant" suggestions to users. 2019 Sep Tutorials, Overviews Beginners Machine Learning Python Recommendation Engine Recommender Systems