Data Science and Beyond

DECEMBER 23, 2018

In my opinion it’s more exciting and relevant to everyday life than more hyped data science areas like deep learning. However, I’ve found it hard to apply what I’ve learned about causal inference to my work. Hence, the book is full of practical examples.

Deep Learning 103

Deep Learning Experimentation Data-driven Data Science 103

KDnuggets

NOVEMBER 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.

Deep Learning 47

Deep Learning Statistics 47

Analytics Vidhya

FEBRUARY 24, 2021

ArticleVideo Book Introduction to Artificial Intelligence and Machine Learning Artificial Intelligence (AI) and its sub-field Machine Learning (ML) have taken the world by storm. The post A Comprehensive Step-by-Step Guide to Become an Industry Ready Data Science Professional appeared first on Analytics Vidhya.

Data Science 321

Data Science Machine Learning Analytics IT 321

Smart Data Collective

AUGUST 20, 2021

Machine Learning Technology Can Be Ideal for Better Monetizing Your Android Apps. The statistic shows that users routinely open 4-6 applications every day. Different apps allow us to chat with friends, order food delivery, book a taxi, and find the best way to the office.

Machine Learning 89

Machine Learning Data mining Advertising Deep Learning 89

Sisense

APRIL 10, 2020

We are surrounded by written text every day: emails, SMS messages, webpages, books, and much more. R is a tool built by statisticians mainly for mathematics, statistics, research, and data analysis. Nowadays text data is huge, so Deep Learning also comes into the picture. NLP can be used on written text or speech data.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

CIO Business Intelligence

AUGUST 11, 2023

How natural language processing works NLP leverages machine learning (ML) algorithms trained on unstructured data, typically text, to analyze how elements of human language are structured together to impart meaning. An NLP algorithm uses this data to find patterns and extrapolate what comes next. NLTK is offered under the Apache 2.0

Unstructured Data 142

Unstructured Data Modeling Machine Learning Data mining 142

Analytics Vidhya

APRIL 11, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Introduction This article is an introduction to autonomous navigation. First, The post Introduction to Autonomous Navigation – LIDAR, Sensor Fusion, Kalman Filter appeared first on Analytics Vidhya.

Data Science 194

Data Science Publishing Analytics Deep Learning 194

Occam's Razor

MARCH 30, 2017

People tend to use these phrases almost interchangeably: Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning. Deep Learning is a specific ML technique. Most Deep Learning methods involve artificial neural networks, modeling how our bran works. All sans human-control.

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

O'Reilly on Data

JULY 28, 2020

Ethics and Data Science is a short book that helps developers think through data problems, and includes a checklist that team members should revisit throughout the process. Some of the best lessons are captured in Ron Kohavi, Diane Tang, and Ya Xu’s book: Trustworthy Online Controlled Experiments : A Practical Guide to A/B Testing.

Marketing 362

Marketing Experimentation Metrics Testing 362

Domino Data Lab

AUGUST 22, 2019

Many thanks to Addison-Wesley Professional for providing the permissions to excerpt “Natural Language Processing” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The excerpt covers how to create word vectors and utilize them as an input into a deep learning model.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

Domino Data Lab

JULY 22, 2019

He was saying this doesn’t belong just in statistics. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. and drop your deep learning model resource footprint by 5-6 orders of magnitude and run it on devices that don’t even have batteries.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Domino Data Lab

MAY 8, 2019

For example, in the case of more recent deep learning work, a complete explanation might be possible: it might also entail an incomprehensible number of parameters. They also require advanced skills in statistics, experimental design, causal inference, and so on – more than most data science teams will have.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

MARCH 3, 2019

O’Reilly Media published our analysis as free mini-books: The State of Machine Learning Adoption in the Enterprise (Aug 2018). The data types used in deep learning are interesting. The data types used in deep learning are interesting. One-fifth use reinforcement learning. will not save you there.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

datapine

NOVEMBER 19, 2019

AI refers to the autonomous intelligent behavior of software or machines that have a human-like ability to make decisions and to improve over time by learning from experience. Currently, popular approaches include statistical methods, computational intelligence, and traditional symbolic AI.

Technology 279

Technology Internet of Things IT IoT 279

Domino Data Lab

JULY 9, 2019

” And this is one of his papers about “you’re doing it wrong” where he talked about the algorithmic culture that he was observing in the machine learning community versus the generative model community that was more traditional in statistics. ” But then I realized I could crowdsource it.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

O'Reilly on Data

JANUARY 25, 2021

This study is based on title usage on O’Reilly online learning. The data includes all usage of our platform, not just content that O’Reilly has published, and certainly not just books. More traditional modes also saw increases: usage of books increased by 11%, while videos were up 24%. AI, Machine Learning, and Data.

Machine Learning 363

Machine Learning Software Testing Technology 363