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.

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Data Science Artificial Intelligence Artificial Intelligence Machine Learning 378

Analytics Vidhya

DECEMBER 19, 2022

Introduction The world is transforming by AI, ML, Blockchain, and Data Science drastically, and hence its community is growing rapidly. So, to provide our community with the knowledge they need to master these domains, Analytics Vidhya has launched its DataHour sessions.

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Dataconomy

MAY 16, 2023

They employ statistical and mathematical techniques to uncover patterns, trends, and relationships within the data. Data scientists possess a deep understanding of statistical modeling, data visualization, and exploratory data analysis to derive actionable insights and drive business decisions.

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Dataversity

SEPTEMBER 25, 2024

How will data visualization evolve in the era of AI/ML? The challenge is to move beyond these unintelligent dashboards to a genuinely transformative visual analytics solution that harnesses the power of AI/ML. While AI is rapidly evolving, it is ironic that business users are still using “dumb” dashboards.

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Analytics Vidhya

AUGUST 2, 2022

This article was published as a part of the Data Science Blogathon. Introduction In the modern day, where there is a colossal amount of data at our disposal, using ML models to make decisions has become crucial in sectors like healthcare, finance, marketing, etc. Many ML models are black boxes since it is difficult to […].

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Analytics Vidhya

JUNE 6, 2022

The ML life cycle helps to build an efficient […]. Introduction The Machine Learning life cycle or Machine Learning Development Life Cycle to be precise can be said as a set of guidelines which need to be followed when we build machine learning-based projects.

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Machine Learning Machine Learning Data Science ML 347

Data Science Dojo

OCTOBER 31, 2024

Growth Outlook: Companies like Google DeepMind, NASA’s Jet Propulsion Lab, and IBM Research actively seek research data scientists for their teams, with salaries typically ranging from $120,000 to $180,000. With the continuous growth in AI, demand for remote data science jobs is set to rise.

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Towards AI

AUGUST 7, 2024

From Solo Notebooks to Collaborative Powerhouse: VS Code Extensions for Data Science and ML Teams Photo by Parabol | The Agile Meeting Toolbox on Unsplash In this article, we will explore the essential VS Code extensions that enhance productivity and collaboration for data scientists and machine learning (ML) engineers.

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Analytics Vidhya

AUGUST 10, 2023

Introduction In today’s evolving landscape, organizations are rapidly scaling their teams to harness the potential of AI, deep learning, and ML. What started as a modest concept, machine learning, has now become indispensable across industries, enabling businesses to tap into unprecedented opportunities.

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Machine Learning Machine Learning Deep Learning Deep Learning 271

KDnuggets

OCTOBER 16, 2019

Also: Kannada-MNIST: A new handwritten digits dataset in ML town; Math for Programmers; The 4 Quadrants of Data Science Skills and 7 Principles for Creating a Viral Data Visualization; The Last SQL Guide for Data Analysis You’ll Ever Need.

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Analytics Vidhya

NOVEMBER 6, 2020

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 264

Data Science Artificial Intelligence Artificial Intelligence Machine Learning 264

Data Science Dojo

FEBRUARY 23, 2024

GPTs for Data science are the next step towards innovation in various data-related tasks. These are platforms that integrate the field of data analytics with artificial intelligence (AI) and machine learning (ML) solutions. You can upload your data files to this GPT that it can then analyze.

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Dataconomy

MAY 2, 2023

The machine learning systems developed by Machine Learning Engineers are crucial components used across various big data jobs in the data processing pipeline. Additionally, Machine Learning Engineers are proficient in implementing AI or ML algorithms. Is ML engineering a stressful job?

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ML ML Machine Learning Machine Learning 110

Dataconomy

MARCH 17, 2025

Augmented analytics is revolutionizing how organizations interact with their data. By harnessing the power of machine learning (ML) and natural language processing (NLP), businesses can streamline their data analysis processes and make more informed decisions. What is augmented analytics?

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Dataversity

JULY 28, 2021

These individuals hold a wide range of positions in the enterprise, from executive and business roles through to data, business, operations, marketing, and sales analyst roles. The post Rise of the Cyborgs: Using AI/ML to Enhance Human Intelligence (Part 1) appeared first on DATAVERSITY.

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Data Science Dojo

JULY 17, 2023

It is a powerful tool that can be used to automate many of the tasks involved in data analysis, and it can also help businesses to discover new insights from their data. It has a wide range of machine 6: Tableau Tableau is a data visualization software platform that can be used to create interactive dashboards and reports.

Data Analysis 195

Data Analysis Data Analysis Tableau Machine Learning 195

Towards AI

JUNE 27, 2023

Let’s get started with the best machine learning (ML) developer tools: TensorFlow TensorFlow, developed by the Google Brain team, is one of the most utilized machine learning tools in the industry. This open-source library is renowned for its capabilities in numerical computation, particularly in large-scale machine learning projects.

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Machine Learning Machine Learning ML ML 98

Mlearning.ai

FEBRUARY 19, 2024

Understanding data is like exploring a maze — it’s intricate and full of unexpected twists. But fear not! Python comes to the rescue with… Continue reading on MLearning.ai »

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Data Visualization Python ML ML 98

ODSC - Open Data Science

FEBRUARY 24, 2023

While machine learning frameworks and platforms like PyTorch, TensorFlow, and scikit-learn can perform data exploration well, it’s not their primary intent. There are also plenty of data visualization libraries available that can handle exploration like Plotly, matplotlib, D3, Apache ECharts, Bokeh, etc.

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Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

Data Science Dojo

FEBRUARY 23, 2024

GPTs for Data science are the next step towards innovation in various data-related tasks. These are platforms that integrate the field of data analytics with artificial intelligence (AI) and machine learning (ML) solutions. You can upload your data files to this GPT that it can then analyze.

Data Science 195

Data Science Data Analysis Data Analysis Machine Learning 195

Data Science Dojo

FEBRUARY 23, 2024

Data Analyst Data Analyst is a featured GPT in the store that specializes in data analysis and visualization. You can upload your data files to this GPT that it can then analyze. Other than the advanced data analysis, it can also deal with image conversions. It is capable of writing and running Python codes.

Data Science 195

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Mlearning.ai

FEBRUARY 25, 2023

Several stages of analysis are needed to find insights and make the right decisions related to data, one of which is data visualization. Data visualization is an essential part of the data analysis process, as it helps to make sense of large and complex data sets. Matplotlib anatomy and terminology 2.

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Data Visualization Data Science Python Data Scientist 52

The MLOps Blog

MARCH 20, 2023

Long-term ML project involves developing and sustaining applications or systems that leverage machine learning models, algorithms, and techniques. An example of a long-term ML project will be a bank fraud detection system powered by ML models and algorithms for pattern recognition. 2 Ensuring and maintaining high-quality data.

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ML ML Machine Learning Machine Learning 59

ODSC - Open Data Science

FEBRUARY 2, 2023

Just as a writer needs to know core skills like sentence structure, grammar, and so on, data scientists at all levels should know core data science skills like programming, computer science, algorithms, and so on. As MLOps become more relevant to ML demand for strong software architecture skills will increase as well.

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Dataconomy

JULY 24, 2023

This involves collecting, cleaning, and analyzing large data sets to identify patterns, trends, and relationships that might otherwise be hidden. Even if you don’t have a degree, you might still be pondering, “How to become a data scientist?” This is where data visualization comes in.

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Data Scientist Data Science Data Analyst Machine Learning 172

ODSC - Open Data Science

OCTOBER 28, 2024

Whether businesses use pattern matching, machine learning (ML), or forecasting, their approach will outperform conventional rule-based systems. Data Science Techniques to Use Against Fraudsters There are several data science techniques for preventing and detecting synthetic identity fraud.

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52

Mlearning.ai

MARCH 17, 2023

Daft Punk is one of the grandfathers of modern electronic music — they popularized it in the 2000s and became a mainstream powerhouse in… Continue reading on MLearning.ai »

Data Visualization 52

Data Visualization ML ML Data Science 52

Pickl AI

DECEMBER 3, 2024

In Python, commonly used libraries include: Pandas: For data manipulation and analysis, particularly for handling structured data. Matplotlib/Seaborn: For data visualization. The post ML | Data Preprocessing in Python appeared first on Pickl.AI. NumPy: For numerical operations and handling arrays.

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Python ML ML Exploratory Data Analysis 52

Data Science Dojo

MAY 18, 2023

Experts from the field gathered to discuss and deliberate on various topics related to data and AI, sharing their insights with the attendees. Additionally, how ML Ops is particularly helpful for large-scale systems like ad auctions, where high data volume and velocity can pose unique challenges.

Data Science 195

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Pickl AI

JANUARY 23, 2023

TensorBoard, a large package that is typically overlooked, is included within TensorFlow and is used for data visualization. When working with shareholders, TensorBoard makes it easier to visually represent the data. Theano Theano is one of the fastest and simplest ML libraries, and it was built on top of NumPy.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

AWS Machine Learning Blog

JUNE 22, 2023

Utilizing data streamed through LnW Connect, L&W aims to create better gaming experience for their end-users as well as bring more value to their casino customers. Predictive maintenance is a common ML use case for businesses with physical equipment or machinery assets. We used AutoGluon to explore several classic ML algorithms.

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AWS ML ML Machine Learning 112

Data Science Connect

JULY 24, 2023

Data scientists are often faced with intricate tasks that require highly specialized tools. Whether it’s data visualization, natural language processing, or predictive analytics, Micro-SaaS products are developed with a razor-sharp focus on providing the best-in-class solutions.

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AWS Machine Learning Blog

MAY 29, 2024

The dataset we created consists of image-text pairs, with each image being an infographic, chart, or other data visualization. Fine tune the model After the data is prepared, we upload it to Amazon Simple Storage Service (Amazon S3) as the SageMaker training input. Alfred Shen is a Senior AI/ML Specialist at AWS.

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ML ML AWS Data Visualization 135

AWS Machine Learning Blog

JANUARY 5, 2024

This post was written in collaboration with Bhajandeep Singh and Ajay Vishwakarma from Wipro’s AWS AI/ML Practice. Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models.

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AWS Machine Learning Blog

MARCH 22, 2023

You can use machine learning (ML) to generate these insights and build predictive models. Educators can also use ML to identify challenges in learning outcomes, increase success and retention among students, and broaden the reach and impact of online learning content. Import the Dropout_Academic Success - Sheet1.csv

Machine Learning 98

Machine Learning Machine Learning Data Scientist ML 98

AWS Machine Learning Blog

FEBRUARY 22, 2023

In this post, we discuss how Boomi used the bring-your-own-container (BYOC) approach to develop a new AI/ML enabled solution for their customers to tackle the “blank canvas” problem. Boomi’s ML and data engineering teams needed the solution to be deployed quickly, in a repeatable and consistent way, at scale.

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AWS Machine Learning Blog

DECEMBER 4, 2023

We capitalized on the powerful tools provided by AWS to tackle this challenge and effectively navigate the complex field of machine learning (ML) and predictive analytics. SageMaker is a fully managed ML service. This was a crucial aspect in achieving agility in our operations and a seamless integration of our ML efforts.

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