Topics: 
Jan
2018 Feb
All (101) | Courses, Education (3) | Meetings (19) | News, Features (11) | Opinions, Interviews (22) | Top Stories, Tweets (9) | Tutorials, Overviews (33) | Webcasts & Webinars (4)
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How data science can improve retail
- Mar 1, 2018.
We’re going to take a look at a few surprising ways that data science can increase your sales, both offline and online. - 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
- Justice Can’t Be Colorblind: How to Fight Bias with Predictive Policing
- Feb 28, 2018.
Predictive policing uncovers racial inequity, which it threatens to perpetuate - but, if we turn things around, it also presents an unprecedented opportunity to advance social justice.
- Jupyter Pop-up coming to Boston on March 21
- Feb 28, 2018.
Attend a day-long exploration of Jupyter's best practices and practical use cases in business and industry.
- McKinsey Analytics Online Hackathon, 10 March, 2018
- Feb 28, 2018.
Calling all coders and data scientists to join McKinsey 24-hour hackathon on March 10, 2018. Win All-expenses paid trip to a tech conference of your choice.
- The Current Hype Cycle in Artificial Intelligence
- Feb 28, 2018.
Over the past decade, the field of artificial intelligence (AI) has seen striking developments. As surveyed in, there now exist over twenty domains in which AI programs are performing at least as well as (if not better than) humans.
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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. -
Gainers and Losers in Gartner 2018 Magic Quadrant for Data Science and Machine Learning Platforms
- Feb 27, 2018.
We compare Gartner 2018 Magic Quadrant for Data Science, Machine Learning Platforms vs its 2017 version and identify notable changes for leaders and challengers, including IBM, SAS, RapidMiner, KNIME, Alteryx, H2O.ai, and Domino. - Learn why the future of data science gathers here + save 50%
- Feb 27, 2018.
Open Data Science Conference just released 80% of their schedule and the first round of speakers for ODSC East 2018 in Boston, May 1-4. Learn, train and engage with 200+ world class experts. Save 50% with code KDNUGGETS.
- Google, Verizon, IBM, & Uber Take the Stage at Predictive Analytics World — this June in Vegas
- Feb 27, 2018.
Predictive Analytics World for Business is heading to Las Vegas, NV on June 3-7, 2018 and we're excited about the stellar speaker line-up, a diverse array of industry leading professionals.
- Aspiring Data Scientists – 4 Steps To Get Hired
- Feb 27, 2018.
The most common complaints we see from candidates who have faced rejection are lack of experience, education level requirements, lack of opportunities for Freshers, overly demanding and confusing job role requirements.
- The Great Big Data Science Glossary
- Feb 27, 2018.
To help those new to the field stay on top of industry jargon and terminology, we've put together this glossary of data science terms.
- Applying Machine Learning to DevOps
- Feb 27, 2018.
This article explains the synergy between DevOps and Machine Learning and their applications like tracking application delivery, troubleshooting and triage analytics, preventing production failures, etc.
- Automated Machine Learning – a game changer for Sports Analytics (Mar 15)
- Feb 26, 2018.
Automated Machine Learning is game-changer for sports analytics. Catch DataRobot's webinar on Mar 15, 2018 to find out how.
- PAW for Industry 4.0 – Munich, June 12-13 – Super Early Bird Rates until March 2
- Feb 26, 2018.
Predictive Analytics World for Industry 4.0 is coming to Munich, 12-13 Jun 2018. Find the latest trends and technologies in machine & deep learning for the era of Internet of Things and artificial intelligence. Super Early Bird Rates end Mar 2.
- How Machine Learning is Advancing Data Centers
- Feb 26, 2018.
Big Data revolution led to the explosion in Data Centers, which are consuming energy at increasingly higher rate. This blog reviews 2 standard methods for improving data center efficiency and argues that 3rd method - Machine Learning - is the best solution.
- Top Stories, Feb 19-25: Top 20 Python AI and Machine Learning Open Source Projects; Deep Learning Development with Google Colab, TensorFlow, Keras & PyTorch
- Feb 26, 2018.
Also: Want a Job in Data? Learn This; A Comparative Analysis of Top 6 BI and Data Visualization Tools in 2018; 5 Fantastic Practical Natural Language Processing Resources; Neural network AI is simple
- A powerful new IDE to build, test, and run Apache Spark applications on your desktop for free!
- Feb 23, 2018.
Build enterprise-grade functionally rich Spark applications with the aid of an intuitive drag-and-drop user interface and a wide array of pre-built Spark operators.
- Gartner 2018 Magic Quadrant for Data Science and Machine Learning – Read the report
- Feb 23, 2018.
Read Gartner 2018 Magic Quadrant for Data Science and Machine Learning Platforms, courtesy of Domino, and learn which data science platform is right for your organization and why Domino was named a Visionary.
- The New Neural Internet is Coming
- Feb 23, 2018.
The Generative Adversarial Networks (GANs) are the first step of neural networks technology learning creativity.
- Age of AI Conference 2018 – Day 2 Highlights
- Feb 23, 2018.
Here are some of the highlights from the second day of the Age of AI Conference, February 1, at the Regency Ballroom in San Francisco.
- Control Structures in R: Using If-Else Statements and Loops
- Feb 23, 2018.
Control structures allow you to specify the execution of your code. They are extremely useful if you want to run a piece of code multiple times, or if you want to run a piece a code if a certain condition is met.
- Get the best out of your data – learn how, in London or San Francisco – KDnuggets Offer
- Feb 22, 2018.
Join us in San Francisco or London this Spring the next chapters of the World-renowned Data & Analytics Innovation Summits. Bringing together the top minds in Big Data and Analytics industry. Use code KD200 to get £/$200 off any two-day pass.
- A Guide to Hiring Data Scientists
- Feb 22, 2018.
This article provides a short overview of emerging data scientist types and their unique skillsets, as well as a guide for HR professionals and analytics managers who are looking to hire their first data scientists or build a data science team. Included are an overview of skills for each type and specific questions that can be asked to assess candidates.
- 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.
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A Comparative Analysis of Top 6 BI and Data Visualization Tools in 2018
- Feb 22, 2018.
In this article, we will compare the most commonly used platforms and analyze their main features to help you choose one or several platforms that will provide indispensable aid for your work communication. - Top KDnuggets tweets, Feb 14-20: Neural Network AI is simple. So… Stop pretending you are a genius
- Feb 21, 2018.
#NeuralNetwork #AI is simple. Stop pretending you are a genius; Cartoon: #ValentinesDay or #MachineLearning Problems in 2118; #MachineLearning Top 10 Open Source Projects.
- Stanford online Data Science, Data Mining courses and certificates
- Feb 21, 2018.
With our online graduate courses and certificates, you can earn a higher education credential from Stanford while still maintaining your career.
- Age of AI Conference 2018 – Day 1 Highlights
- Feb 21, 2018.
Here are some of the highlights from the first day of the Age of AI Conference, January 31, at the Regency Ballroom in San Francisco.
- Recommender Engine - Under The Hood
- Feb 21, 2018.
We examine two main types of recommender systems: Content based and Collaborative filtering. Both have their pros and cons depending upon the context in which you want to use them.
- Artificial Intelligence (AI) Conference, April 29 – May 2, 2018, NYC – KDnuggets Offer
- Feb 20, 2018.
Join the leading minds in AI, explore AI latest developments, separate hype from reality, and learn how to apply AI in your organization right now. Use code PCKDNG. Early price ends Mar 16.
- KDnuggets part-time, paid internship in Data Science/Machine Learning Journalism.
- Feb 20, 2018.
KDnuggets is looking for graduate students in AI, Analytics, Data Science, or Machine Learning for a part-time (5-10 hrs/week) paid internship to do data journalism, research and write blogs, and help run KDnuggets site.
- PAW Vegas Early Bird Ends This Friday — Deep Learning and 4 Vertical Events
- Feb 20, 2018.
Predictive Analytics World and Deep Learning World conferences are coming to Caesars Palace in Las Vegas, Jun 3-7. It's not too late to save with the Early Bird and attend the biggest PAW mega-event ever.
- Strata London, May 21-24 (and Strata San Jose, Mar 5-8) – KDnuggets Offer
- Feb 20, 2018.
Strata gives you the tools, skills, and intel to stay ahead in the rapidly evolving field of data. Best price till Fri, Feb 23, 2018. Also, save 20% on Strata San Jose with code KDNU.
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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. - Where AI is already rivaling humans
- Feb 20, 2018.
Since 2011, AI hit hypergrowth, and researchers have created several AI solutions that are almost as good as – or better than – humans in several domains, including games, healthcare, computer vision and object recognition, speech to text conversion, speaker recognition, and improved robots and chat-bots for solving specific problems.
- 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.
- Applied Data Science: Solving a Predictive Maintenance Business Problem Part 2
- Feb 20, 2018.
In this post we will discuss further on how exploratory analysis can be used for getting insights for feature engineering.
- Deep Learning World Vegas – Talks from Cisco, Cap1, Lyft, Qantas, Uber…
- Feb 19, 2018.
The inaugural Deep Learning World heads to Caesar's Palace Las Vegas, Jun 3-7, alongside Predictive Analytics World. Early Bird pricing ends Friday – Register now!
- 5 Things You Need To Know About Data Science
- Feb 19, 2018.
Here are 5 useful things to know about Data Science, including its relationship to BI, Data Mining, Predictive Analytics, and Machine Learning; Data Scientist job prospects; where to learn Data Science; and which algorithms/methods are used by Data Scientists
- Graph Databases Burst into the Mainstream
- Feb 19, 2018.
What do Amazon, Facebook, Google, IBM, Microsoft and Twitter have in common? They're all adopters of graph databases - a hot technology that continues to evolve.
- Top Stories, Feb 12-18: Neural network AI is simple; Data Science at the Command Line: Exploring Data
- Feb 19, 2018.
Also: A Basic Recipe for Machine Learning; Histogram 202: Tips and Tricks for Better Data Science; Calculating Customer Lifetime Value: SQL Example
- Want a Job in Data? Learn This
- Feb 19, 2018.
Why mastering a 50-year-old programming language is the key to getting a data science job.
- The Data Scientist’s Guide to Apache Spark™
- Feb 16, 2018.
How data scientists can leverage Spark for advanced analytics.
- Logistic Regression: A Concise Technical Overview
- Feb 16, 2018.
Interested in learning the concepts behind Logistic Regression (LogR)? Looking for a concise introduction to LogR? This article is for you. Includes a Python implementation and links to an R script as well.
- Resurgence of AI During 1983-2010
- Feb 16, 2018.
We discuss supervised learning, unsupervised learning and reinforcement learning, neural networks, and 6 reasons that helped AI Research and Development to move ahead.
- Big Data: Promises, Challenges and Threats
- Feb 16, 2018.
Marketing researchers are wondering what lies ahead for big data. Marketing Scientist Kevin Gray asks Professor Koen Pauwels for his thoughts.
- 2018 IEEE Big Data Cup
- Feb 16, 2018.
The IEEE Big Data conference series started in 2013 has established itself as the top tier research conference in Big Data. We invite industrial, government, and academic organizations to submit proposals to organize a Data Challenge for the 2018 IEEE International Conference on Big Data.
- Preventing Claims with Automation, IoT and Connected Services (Webinar, Feb 23)
- Feb 15, 2018.
This webinar will give you the insights to stay ahead of the curve of innovation, including Real-Time Risk Assessment, Automatically Turning Data to Action, and more.
- Build Your Skills in the Career You Love – KDnuggets Offer
- Feb 15, 2018.
In the spirit of Valentine's Day, we want to show you the love - data love. Use coupon KDLOVE25 and save 25% on all individual Online Learning courses*, now through February 26!
- Histogram 202: Tips and Tricks for Better Data Science
- Feb 15, 2018.
We show how to make an ideal histogram, share some tips, and give examples. Let's dive into the world of binning.
- Neural network AI is simple. So… Stop pretending you are a genius
- Feb 15, 2018.
This post may come off as a rant, but that’s not so much its intent, as it is to point out why we went from having very few AI experts, to having so many in so little time.
- Calculating Customer Lifetime Value: SQL Example
- Feb 15, 2018.
In order to understand how to estimate LTV, it is useful to first think about evaluating a customer’s lifetime value at the end of their relationship with us.
- Feel the Data Science Love at AnacondaCON 2018
- Feb 14, 2018.
At AnacondaCON 2018, Apr 8-11 in Austin, our passionate community of data scientists, IT professionals, analysts, developers, and business leaders will come together for 45+ talks on data science, machine learning, AI, and more. Early Bird offer - 2 tickets for price of one before Feb 28!
- Top KDnuggets tweets, Feb 7–13: Fundamentals of #MachineLearning and #DeepLearning in #Python using Scikit-Learn and #TensorFlow
- Feb 14, 2018.
Also: Transfer Learning using differential learning rates; Which #MachineLearning #Algorithm be used in year 2118? We explain why it will be #Regression; 5 Fantastic Practical #MachineLearning Resources
- Cartoon: Machine Learning Problems in 2118
- Feb 14, 2018.
For Valentine's day, new KDnuggets cartoon looks at some problems Machine Learning can face in 2118.
- 3 principles for solving AI Dilemma: Optimization vs Explanation
- Feb 14, 2018.
We propose 3 principles for maximizing the benefits of machine learning without sacrificing its intelligence.
- Data Science at the Command Line: Exploring Data
- Feb 14, 2018.
See what's available in the freely-available book "Data Science at the Command Line" by digging into data exploration in the terminal.
- New Keynotes Added for Marketing Analytics and Data Science 2018
- Feb 13, 2018.
Join MADS: Marketing Analytics and Data Science in San Francisco, Apr 11-13, hear first-hand from industry thought leaders and experts on how to navigate the challenges and succeed at making data work for YOU! Save 20% with VIP Code MADS18KDN
- Insurance AI – the roadmap to impact (exclusive whitepaper Blue Cross, Zurich, Unum & CCA Global Partners)
- Feb 13, 2018.
Understanding where and how AI will impact insurance is crucial to deliver growth and true business value. Download the whitepaper “Insurance AI – The Roadmap to Impact” which includes partners' AI plans for 2020 and which steps they are taking today to achieve this vision.
- The Birth of AI and The First AI Hype Cycle
- Feb 13, 2018.
A dazzling review of AI History, from Alan Turing and Turing Test, to Simon and Newell and Logic Theorist, to Marvin Minsky and Perceptron, birth of Rule-based systems and Machine Learning, Eliza - first chatbot, Robotics, and the bust which led to first AI Winter.
- Building a Toy Detector with Tensorflow Object Detection API
- Feb 13, 2018.
This project is second phase of my popular project - Is Google Tensorflow Object Detection API the easiest way to implement image recognition? Here I extend the API to train on a new object that is not part of the COCO dataset.
- A Basic Recipe for Machine Learning
- Feb 13, 2018.
One of the gems that I felt needed to be written down from Ng's deep learning courses is his general recipe to approaching a deep learning algorithm/model.
- 7 Steps of a Data Science PoC – Get The Guidebook
- Feb 12, 2018.
Download a free copy of the white paper The 7 Steps to Driving a Successful Data Science POC for a detailed walk-through of the seven steps to running a successful POC.
- Last chance to register to attend DataScience: Elevate in San Francisco
- Feb 12, 2018.
DataScience: Elevate will be held Feb 22 in San Francisco. Register to be a part of a full day of panels and presentations from people and companies at the forefront of data science.
- Interview: Bill Moreau, USOC on Empowering World’s Best Athletes through Analytics.
- Feb 12, 2018.
CNBC recently quoted this KDnuggets interview which discussed how United States Olympic Committee uses Big Data, how athletes respond to Analytical insights, integration of sports medicine into sports performance and sports injury.
- 4 Things You Probably Didn’t Know Machine Learning and AI was used for
- Feb 12, 2018.
AI was compared to the discovery of fire, but its impact hinges on how creative we are with the technology—just like it did for early humans employing fire. Here are four diverse examples of applied AI to get your creative juices flowing.
- Top Stories, Feb 5-11: 5 Fantastic Practical Machine Learning Resources; A Simple Starter Guide to Build a Neural Network
- Feb 12, 2018.
Also: Introduction to Python Ensembles; 5 Machine Learning Projects You Should Not Overlook; Top 15 Scala Libraries for Data Science in 2018; Fast.ai Lesson 1 on Google Colab (Free GPU); The Doing Part of Learning Data Science
- 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.
- Hear from leading thinkers in Analytics and Data Science at Data Day 2018, Australia
- Feb 11, 2018.
The one-day conference includes 16 sessions across dedicated streams focusing on data and analytics, technology, customer experience & marketing strategy: Melbourne 23 Feb, Sydney 26 Feb.
- Expanding Self-Service BI with AI-Powered Analytics, Feb 22
- Feb 9, 2018.
Learn how AI and machine learning technology will expand adoption of service-service BI by making it easier for business users to answer ad hoc questions and perform advanced analysis on their own.
- Which Machine Learning Algorithm be used in year 2118?
- Feb 9, 2018.
So what were the answers popping in your head ? Random forest, SVM, K means, Knn or even Deep Learning? No, for the answer, we turn to Lindy Effect.
- 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.
- Top 15 Scala Libraries for Data Science in 2018
- Feb 9, 2018.
For your convenience, we have prepared a comprehensive overview of the most important libraries used to perform machine learning and Data Science tasks in Scala.
- Join RE•WORK & AI experts in London, Boston and Hong Kong – KDNUGGETS discount
- Feb 8, 2018.
Miss RE•WORK in San Francisco? Join AI and deep learning experts in London, Hong Kong or Boston, and save 25% with the code KDNUGGETS.
- Why Data Scientists Must Know About Change Management
- Feb 8, 2018.
Change management may be seen as an opposite to data science, but in reality both are related. Without proper implementation, a data science project fails.
- 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!
- Fast.ai Lesson 1 on Google Colab (Free GPU)
- Feb 8, 2018.
In this post, I will demonstrate how to use Google Colab for fastai. You can use GPU as a backend for free for 12 hours at a time. GPU compute for free? Are you kidding me?
- Top KDnuggets tweets, Jan 31 – Feb 6: #DeepLearning for Natural Language Processing: Tutorials with Jupyter Notebooks
- Feb 7, 2018.
Also: Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples; Why Generalists Dominate #DataScience - an inconvenient truth; #ICYMI A Beginner’s Guide to Data Engineering – Part I
- AI & Machine Learning: the key skills every software engineer needs in 2018
- Feb 7, 2018.
Designed specifically by, and for, senior software engineers, architects, and technical engineering managers, QCon.ai is a dedicated conference for AI and machine learning. Use code KDnuggets by Feb 17 to save.
- Building a Daily Bitcoin Price Tracker with Coindeskr and Shiny in R
- Feb 7, 2018.
This tutorial is to help an R user build his/her own Daily Bitcoin Price Tracker using three packages, Coindeskr, Shiny and Dygraphs.
- Deep Feature Synthesis: How Automated Feature Engineering Works
- Feb 7, 2018.
Automating feature engineering optimizes the process of building and deploying accurate machine learning models by handling necessary but tedious tasks so data scientists can focus more on other important steps.
- NYU Stern MS in Business Analytics
- Feb 6, 2018.
Are you ready to take the next step forward in your career? Apply now for NYU Stern's MS in Business Analytics (MSBA) program.
- Register for DataScience: Elevate Livestream, Feb 22
- Feb 6, 2018.
DataScience: Elevate will be held Feb 22 in San Francisco. Register now for the livestream to tune into a full day of panels and presentations from people and companies at the forefront of data science.
- Top January Stories: Docker for Data Science; Top 10 TED Talks for Data Scientists and Machine Learning Engineers
- Feb 6, 2018.
Also: Quantum Machine Learning: An Overview; Comparing Machine Learning as a Service: Amazon, Microsoft Azure, Google Cloud AI
- 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?
- 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.
- The Doing Part of Learning Data Science
- Feb 6, 2018.
Consider this a beginner’s answer to “Studied Basics, What Next?”
- Future Trends in Biometrics
- Feb 5, 2018.
Biometric identification is moving from the realm of high -tech movie scenes to everyday use. The science is already changing physical and cyber security.
- Challenge Yourself to Think, Mar 19-22, Las Vegas
- Feb 5, 2018.
Think 2018 is for those who seek inspiration and education, reinvention and innovation, want to connect with experts and seek progress. It is for understanding what is going on in the world around AI, Cloud, Data, Security, and Systems and discovering what’s possible. Use code TK18CAC to save.
- Top Stories, Jan 29 – Feb 4: Web Scraping Tutorial with Python: Tips and Tricks; Data Structures Related to Machine Learning Algorithms
- Feb 5, 2018.
Also: The 8 Neural Network Architectures Machine Learning Researchers Need to Learn; Avoid Overfitting with Regularization; Understanding Learning Rates and How It Improves Performance in Deep Learning; Comparing Machine Learning as a Service
- 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.
- Upcoming Meetings in AI, Analytics, Big Data, Data Science, Deep Learning, Machine Learning: February and Beyond
- Feb 2, 2018.
Coming soon: TDWI Las Vegas, BI + Analytics Huntington Beach, Strata San Jose, IBM Think Las Vegas, Big Data & Analytics Singapore, KNIME Berlin, Nvidia GPU, and more.
- Generalists Dominate Data Science
- Feb 2, 2018.
An interesting insight into why small teams generalists outperform large teams of specialists.
- Avoid Overfitting with Regularization
- Feb 2, 2018.
This article explains overfitting which is one of the reasons for poor predictions for unseen samples. Also, regularization technique based on regression is presented by simple steps to make it clear how to avoid overfitting.
- The Future of Data and Analytics is Coming to TDWI Chicago
- Feb 1, 2018.
Registration is open for TDWI's annual Chicago Conference. KDnuggets readers save 30% through February 28 with priority code KD30. Register now!
- Enhancing Customer 360 Models with Automated Machine Learning
- Feb 1, 2018.
Join DataRobot on Feb 15 to discover how Automated Machine Learning provides the ability to develop and refresh Customer 360 predictive models, the ability to deploy models with a click of a button, and more!
- 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.
- The AGI/Deep Learning Connection
- Feb 1, 2018.
Also, deep learning would definitely prove to be an essential component to create truly intelligent machines but probably not enough alone.
- Understanding Learning Rates and How It Improves Performance in Deep Learning
- Feb 1, 2018.
Furthermore, the learning rate affects how quickly our model can converge to a local minima (aka arrive at the best accuracy). Thus getting it right from the get go would mean lesser time for us to train the model.
- The 8 Neural Network Architectures Machine Learning Researchers Need to Learn
- Jan 31, 2018.
In this blog post, I want to share the 8 neural network architectures from the course that I believe any machine learning researchers should be familiar with to advance their work.
How to Think Like a Data Scientist or Data Analyst
Python For Everybody: The Free eBook