Maurice

150 Added | 2 Magazines | 2 Likes | 6 Following | 9 Followers | @mauricecream | Always on the lookout for ice cream. Young & enthusiastic #BigData IT business professional learning #DataScience. Entrepreneurial drive & #analytical mindset.

It's Not About Just the Experience, It's the Journey -- With Analytics

Thanks to dramatic new algorithms, you're about to learn a whole lot more about your customer's actions and preferences.<p>Today's businesses want to create exceptional customer experiences. They mine big data to get a good sense of direction. Yet while this effort produces plenty of statistics, it …

Number plate detection with Supervisely and Tensorflow (Part 1)

Deep learning is widely used nowadays. There are a lot of interesting applications of neural networks in computer vision tasks. This tutorial will …

10 hot data analytics trends — and 5 going cold

Data analytics are fast becoming the lifeblood of IT. Big data, machine learning, deep learning, data science — the range of technologies and …

Introducing Vectorflow

a lightweight neural network library for sparse data<p>By Benoît Rostykus<p><b>Introduction</b><p>With the deluge of deep learning libraries and software innovation …

Why the future of deep learning depends on finding good data

We’ve already taken a look at neural networks and deep learning techniques in a previous post, so now it’s time to address another major component of deep learning: data — meaning the images, videos, emails, driving patterns, phrases, objects and so on that are used to train neural …

Data Science Simplified Part 2: Key Concepts of Statistical Learning

In the first article of this series, I had touched upon key concepts and processes of Data Science. In this article, I will dive in a bit deeper. …

Neural networks for algorithmic trading. Multimodal and multitask deep learning

Here we are again! We already have four tutorials on financial forecasting with artificial neural networks where we compared different architectures …

Pandas/scikit-learn: get_dummies Test/Train Sets

I’ve been using panda’s get_dummies function to generate dummy columns for categorical variables to use with scikit-learn, but noticed that it …

Data Science

Building an analytics and reporting stack in 2017 — Reflect Blog

We spoke with over 50 Reflect customers across 10 industries to find out which analytics stacks are working and which are not. Here are the biggest …

Big Data

Will big data change how you use social media?

Anyone who is confused by this term should simply look at the name for an answer. Big data is exactly what it sounds like: massive volumes of data.<p>Businesses are concerned with big data because it requires new methods of interaction. Every part of the process including collecting, storing, and …

Big Data

What I learned recruiting young data scientists for our 500-year-old company

Data scientists will often receive at least one new message a week from a recruiter about a potential new role for them, with the really good …

Alibaba: Building a retail ecosystem on data science, machine learning, and cloud

What does it take to compete in a global arena in which retail and cloud are increasingly intertwined? Domain-specific data science and machine …

eCommerce

The top 19 big data and data analytics certifications for 2017

Data and big data analytics are fast becoming the lifeblood of any successful business. Getting the technology right can be challenging, but building …

Stock Trading Analytics and Optimization in Python with PyFolio, R’s PerformanceAnalytics, and backtrader

(This article was first published on <b>R – Curtis Miller's Personal Website</b>, and kindly contributed to R-bloggers)<p>Introduction<p>Having figured out how to …

CS231n Convolutional Neural Networks for Visual Recognition

Spring 2017 Assignments<p>Module 0: Preparation<p>Module 1: Neural Networks<p>L1/L2 distances, hyperparameter search, cross-validation<p>parameteric approach, …

Deep Learning

How to build a data science pipeline

Start with y. Concentrate on formalizing the predictive problem, building the workflow, and turning it into production rather than optimizing your …

3 Key Trends Shaping the 2017 Data Science Hiring Market

<i>This post is an adapted excerpt from our newly-released report, The Burtch Works Study: Salaries of Data Scientists 2017, which examines updated</i> …

How to Integrate Data and Analytics into Every Part of Your Organization

Many conversations about data and analytics (D&A) start by focusing on technology. Having the right tools is critically important, but too often executives overlook or underestimate the significance of the people and organizational components required to build a successful D&A function.<p>When that …

Management

Data Scientist Resume Projects – Stats and Bots

Data scientists are one of the most hirable specialists today, but it’s not so easy to enter this profession without a “Projects” field in your …

Google’s Tensor2Tensor makes it easier to conduct deep learning experiments

Google’s brain team is open sourcing Tensor2Tensor, a new deep learning library designed to help researchers replicate results from recent papers in the field and push the boundaries of what’s possible by trying new combinations of models, datasets and other parameters. The sheer number of …

Machine Learning

dplyr 0.7.0

I’m pleased to announce that dplyr 0.7.0 is now on CRAN! (This was dplyr 0.6.0 previously; more on that below.) dplyr provides a “grammar” of data …

Data Science

Will big data create a new untouchable business elite?

Dark side of the boon<p><b>Will the ascent of artificial intelligence (AI) and machine learning built by big data create an unstoppable inequality of</b> …

Creating a Better Economy with Data Science (Blog)

By Martin Whittaker & Tianhui Michael LiWe need to channel capital in all its forms in a direction where it can have a lasting impact and generate …

Data Science

3 Things Are Holding Back Your Analytics, and Technology Isn’t One of Them

During the past decade, business analytics platforms have evolved from supporting IT and finance functions to enabling business users across the enterprise. But many firms find themselves struggling to take advantage of its promise. We’ve found three main obstacles to realizing analytics’ full …

Databricks brings deep learning to Apache Spark

Databricks is giving users a set of new tools for big data processing with enhancements to Apache Spark. The new tools and features make it easier to do machine learning within Spark, process streaming data at high speeds, and run tasks in the cloud without provisioning servers.<p>On the machine …

Big Data

Data science scratchpad

I spent the last computer-week working solely on data science, that mixed, applied practice of statistics, exploratory data analysis, machine …

Python Programming

J.P.Morgan’s massive guide to machine learning and big data jobs in finance

So you want to work in machine learning and big data in finance? In 2017, J.P. Morgan issued a huge new report on that.

J.P. Morgan

I Want to Surrender to Cambridge Analytica

This Big Brother is more sclerotic than sinister -- and needs our help.<p>The theory that a sinister big data firm called Cambridge Analytica (and some associated companies) played a major role in the election of U.S. President Donald Trump and the Brexit vote is remarkably persistent despite some …

Cambridge Analytica

Automated Machine Learning — A Paradigm Shift That Accelerates Data Scientist Productivity @ Airbnb

By Hamel Husain & Nick Handel<p>At Airbnb, we are always searching for ways to improve our data science workflow. A fair amount of our data science …

Machine Learning

Of These Top 20 Free Analytics Tools My Favorite is (Drum Roll, Please...)

Of These Top 20 Free Analytics Tools My Favorite is (Drum Roll, Please…)<p>Just last week, Sam Scott published a very helpful article called “16 Free …