Insight

AUGUST 12, 2019

For a good overview of what DevOps entails and how to transition, check out this blog post. The activities within each category are ranked more or less in order of importance as well. if you don’t have a strong preference, I recommend Python) and practice, practice, practice. I suggest Python, but you can work in any language.

Software 65

Software Data-driven Testing Interactive 65

Sisense

SEPTEMBER 3, 2020

Besides strong technical skills (for instance, use of Hadoop, programming in R and Python , math, statistics), data scientists should also be able to tackle open-ended questions and undirected research in ways that bring measurable business benefits to their organization. We live in a constantly-evolving world of data.

Statistics 97

Statistics Metrics Visualization Finance 97

IBM Big Data Hub

AUGUST 28, 2023

Text classification: Useful for tasks like sentiment classification, spam filtering and topic classification, text classification involves categorizing documents into predefined classes or categories. Using programming languages like Python with high-tech platforms like NLTK and SpaCy, companies can analyze user-generated content (e.g.,

Data mining 56

Data mining Machine Learning Deep Learning Marketing 56

Insight

JANUARY 14, 2020

Pillow is a fork of the Python Imaging Library (PIL), and is along the same lines as OpenCV. Keras is an open source deep learning API that was written in Python and runs on top of Tensorflow, so it’s a little more user-friendly and high-level than Tensorflow. You can view the documentation and check out a quick tutorial.

Metrics 58

Metrics Optimization Modeling Testing 58

Domino Data Lab

JANUARY 6, 2019

And my favorite topic: what are some of the best books, blogs, podcasts, etc., or Julia (winner of 2018 Wilkinson prize ), most people are focusing on Python for introduction to data science. There are oh-so-many good blogs about data science, and one of my top picks is the go-to site for data visualization, Flowingdata.

Data Science 56

Data Science Machine Learning Reporting Visualization 56

AWS Big Data

FEBRUARY 21, 2024

For the connection name, enter MWAA-Glue-Blog-Subnet1. Repeat these steps using PrivateSubnet2 and name the connection MWAA-Glue-Blog-Subnet2. Replace the placeholder script with the following Python code: import ipaddress import socket subnets = { "PrivateSubnet1": "10.192.20.0/24", Use the default security group. Choose Next.

Strategy 91

Strategy Management Visualization IT 91

Domino Data Lab

AUGUST 12, 2021

In a previous blog , we have covered how Pandas Profiling can supercharge the data exploration required to bring our data into a predictive modelling phase. For example, are the numbers we are seeing actually referring to categories or are the dates provided in a specific format? Python and Pandas Profiling.

Machine Learning 126

Machine Learning Reporting Statistics Visualization 126

Domino Data Lab

JULY 15, 2021

While there are certainly engineers and scientists who may be entrenched in one camp or another (the R camp vs. Python, for example, or SAS vs. MATLAB), there has been a growing trend towards dispersion of data science tools. Key categories of tools and a few examples include: Data Sources. They range from flat files (e.g.

Data Science 145

Data Science Visualization Modeling Enterprise 145

AWS Big Data

SEPTEMBER 20, 2023

Install AWS CLI and Python library Install and configure the AWS Command Line Interface (AWS CLI) if you don’t have it already set up. Optionally, if you want to use run a local notebook from your computer, install Python 3.7 For Service category , select AWS services. Choose Create subnet. 24 ), and create your subnet.

Interactive 94

Interactive Management Reporting IT 94

DataKitchen

APRIL 13, 2021

Read the complete blog below for a more detailed description of the vendors and their capabilities. Because it is such a new category, both overly narrow and overly broad definitions of DataOps abound. Studio.ML — A model management framework written in Python to help simplify and expedite your model-building experience.

Testing 307

Testing Machine Learning Consulting Data Quality 307

AWS Big Data

JUNE 19, 2023

It’s a portable columnar format, future proofed to support additional encodings as technology develops, and it has library support across a broad set of languages like Python, Java, and Go. For this post, we name the stack blog-lambda. And the best part is that Apache Parquet is open source! Choose Next. Enter a name for your stack.

Publishing 83

Publishing Dashboards Visualization Management 83

Sisense

JUNE 26, 2020

Both Python and R are advanced coding languages that can produce beautiful images that allow humans to understand vast datasets with ease. Data Visualization in Python. There are a wide array of libraries you can use to create Python data visualizations, including Matplotlib, seaborn, Plotly , and others. Import Libraries.

Visualization 97

Visualization Unstructured Data Measurement Data-driven 97

Cloudera

APRIL 11, 2023

For the Cloudera and AMD Applied Machine Learning Prototype Hackathon , competitors were tasked with creating their own unique AMP for one of five categories (Sports and Entertainment, Environment, Business and Economy, Society, and Open Innovation). As you can tell, we left the guidance pretty open ended.

Forecasting 72

Forecasting Machine Learning Recreation/Entertainment Sales 72

Sisense

SEPTEMBER 25, 2020

In this article, we will explain how to execute five statistical techniques using Python. Code: Let’s see Python code implementation of logistic regression on an Amazon fine food reviews dataset. In Next-Level Moves , we dig into the ways advanced analytics are paving the way for the next wave of innovation.

Statistics 98

Statistics Modeling Predictive Modeling Machine Learning 98

Cloudera

OCTOBER 17, 2023

This blog is for anyone who was interested but unable to attend the conference, or anyone interested in a quick summary of what happened there. Operationalizing python for real-time ML pipelines was a hot topic. The post 5 Key Takeaways from #Current2023 appeared first on Cloudera Blog.

Data-driven 75

Data-driven Enterprise IoT Data Warehouse 75

Sisense

APRIL 13, 2020

Or perhaps instead they prefer to hone their skills in SQL , Python, or R. In Navigating Change in Crisis, we explore how individuals and companies are adapting to a “new normal” to keep essential services functioning. These insights aim to help you and your team navigate these unprecedented times.

Uncertainty 83

Uncertainty Marketing Digital Transformation Forecasting 83

Insight

MARCH 25, 2020

In this blog, I will share how I built Pair , a scalable web application that takes in a product image, analyzes its design features using convolutional neural network, and recommends products in other categories with similar style elements. Multiple such index libraries are generated for different furniture categories.

Deep Learning 53

Deep Learning Metrics Data Processing Interactive 53

Insight

MARCH 4, 2020

In this blog, I’ll describe how to solve this with Contextual Topic Identification, leveraging machine learning methods to identify semantically similar groups and surface relevant category tags of the reviews. Then, leveraging Python frameworks, I implemented the topic identification models.

Visualization 81

Visualization Modeling Metrics Measurement 81

O'Reilly on Data

NOVEMBER 28, 2023

But that isn’t all the art that a company needs: “hero images” for blog posts, designs for reports and whitepapers, edits to publicity photos, and more are all necessary. The LLaMA-family models also fall into the “so-called open source” category that restricts what you can build. Is generative AI the answer? Perhaps not yet.

Enterprise 269

Enterprise Modeling Testing Reporting 269

Domino Data Lab

JULY 22, 2019

This blog post provides a concise session summary, a video, and a written transcript. It may be that for people in the former category, if they don’t level up to it, well, there are some good construction jobs. They can use Python and Jupyter to deploy apps in machine learning that the bank needs, on day one.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

AWS Big Data

NOVEMBER 6, 2023

Amazon EMR Studio is an integrated development environment (IDE) that makes it straightforward for data scientists and data engineers to develop, visualize, and debug data engineering and data science applications written in R, Python, Scala, and PySpark. For instruction, please refer to Create a data lake administrator.

Data Lake 92

Data Lake Sales Management Testing 92

The Unofficial Google Data Science Blog

AUGUST 31, 2016

By DAVID ADAMS Since inception, this blog has defined “data science” as inference derived from data too big to fit on a single computer. Thus it is easy to use Spark for interactive analysis (from a python or scala shell) and to prototype ML algorithms but harder to do so in Dataflow. map( lambda x: convert_line(x.

Data Science 66

Data Science Sales Optimization Cost-Benefit 66

Smart Data Collective

OCTOBER 14, 2019

When Google talked about releasing this tool in its blog, the brand pointed out that if you don’t protect user data, you risk losing people’s trust. Plotly Python Open Source Graphing Library. The website breaks down the types of charts into categories. Kubernetes. Alternatively, Plotly offers geographical maps.

Data Science 67

Data Science Machine Learning Big Data Interactive 67

Domino Data Lab

DECEMBER 2, 2020

In this blog post, I will cover a family of techniques known as density-based clustering. Using these two parameters, DBSCAN categories the data points into three categories: Core Points : A data point p is a core point if Nbhd ( p , ? ) [?-neighborhood Border Points: A data point *q is a border point if Nbhd ( q , ?

Metrics 116

Metrics KDD Testing Machine Learning 116

DataRobot Blog

MARCH 9, 2022

The only caveat is that they must be adapted to classify inputs into one of n emotional categories rather than a binary positive or negative. Coursera – Applied Text Mining in Python video demonstration. Further reading. MonkeyLearn – A guide to sentiment analysis functions and resources.

Machine Learning 52

Machine Learning Deep Learning Modeling Measurement 52

Domino Data Lab

JULY 1, 2021

In this blog post we present the Named Entity Recognition problem and show how a BiLSTM-CRF model can be fitted using a freely available annotated corpus and Keras. The categories that the named entities are classified into are predefined and often contain entries like locations, organisations, job types, personal names, times and others.

Modeling 111

Modeling Statistics Testing Metrics 111

Business Over Broadway

DECEMBER 20, 2018

All of my top blog posts of 2018 (most reads) are all related to data science, with posts that address the practice of data science, artificial intelligence and machine learning tools and methods that are commonly used and even a post on the problems with the Net Promoter Score claims. Click image to enlarge.

Machine Learning 74

Machine Learning Data Science Deep Learning Predictive Analytics 74

The Unofficial Google Data Science Blog

MARCH 13, 2017

By MUKUND SUNDARARAJAN, ANKUR TALY, QIQI YAN Editor's note: Causal inference is central to answering questions in science, engineering and business and hence the topic has received particular attention on this blog. It takes an image as input and assigns scores for 1000 different ImageNet categories.

IT 68

IT Visualization Modeling Uncertainty 68

The Data Visualisation Catalogue

APRIL 24, 2024

Additionally, colour can be used to represent different categories or an additional variable. This method ensures all data points remain visible, enhancing the visibility of density and variation.

Snapshot 88

Snapshot Visualization 88

Alation

FEBRUARY 17, 2023

In this blog, I’ll address some of the questions we did not have time to answer live, pulling from both Dr. Reichental’s book as well as my own experience as a data governance leader for 30+ years. And for good rason: many data governance jobs postings seek skills like Python, programming skills, etc. Curious to hear from the author?

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

The Data Visualisation Catalogue

MARCH 26, 2024

It is particularly effective for comparing quantitative value ranges across different categories, offering a clear visualisation of the differences or changes between them. The categories or groups are typically represented along one axis, while the quantitative values are plotted along the other axis.

Snapshot 85

Snapshot Visualization IT 85