Pickl AI

JANUARY 29, 2024

Summary: In the tech landscape of 2024, the distinctions between Data Science and Machine Learning are pivotal. Data Science extracts insights, while Machine Learning focuses on self-learning algorithms. The collective strength of both forms the groundwork for AI and Data Science, propelling innovation.

Data Science 52

Data Science ML Machine Learning Artificial Intelligence 52

Analytics Vidhya

JUNE 12, 2023

Introduction Meet Tajinder, a seasoned Senior Data Scientist and ML Engineer who has excelled in the rapidly evolving field of data science. Tajinder’s passion for unraveling hidden patterns in complex datasets has driven impactful outcomes, transforming raw data into actionable intelligence.

Data Scientist 272

Data Scientist Machine Learning Actionable Intelligence ML Engineer 272

ODSC - Open Data Science

FEBRUARY 2, 2023

Here’s what we found for both skills and platforms that are in demand for data scientist jobs. Data Science Skills and Competencies Aside from knowing particular frameworks and languages, there are various topics and competencies that any data scientist should know. Joking aside, this does infer particular skills.

Data Science 98

Data Science Data Scientist Big Data Machine Learning 98

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.

Data Science 110

Data Science Data Drift DevOps Auto-complete 110

Analytics Vidhya

FEBRUARY 21, 2022

This article was published as a part of the Data Science Blogathon. Image designed by the author – Shanthababu Introduction Every ML Engineer and Data Scientist must understand the significance of “Hyperparameter Tuning (HPs-T)” while selecting your right machine/deep learning model and improving the performance of the model(s).

ML Engineer 320

ML Engineer Data Scientist Deep Learning Data Science 320

Analytics Vidhya

OCTOBER 22, 2021

This article was published as a part of the Data Science Blogathon Introduction Working as an ML engineer, it is common to be in situations where you spend hours to build a great model with desired metrics after carrying out multiple iterations and hyperparameter tuning but cannot get back to the same results with the […].

Machine Learning 312

Machine Learning ML Engineer Data Science ML 312

ODSC - Open Data Science

FEBRUARY 9, 2023

It is often too much to ask for the data scientist to become a domain expert. However, in all cases the data scientist must develop strong domain empathy to help define and solve the right problems. Nina Zumel and John Mount, Practical Data Science with R, 2nd Ed.

Data Scientist 105

Data Scientist Machine Learning ML Engineer ML 105

AWS Machine Learning Blog

SEPTEMBER 20, 2023

In these scenarios, as you start to embrace generative AI, large language models (LLMs) and machine learning (ML) technologies as a core part of your business, you may be looking for options to take advantage of AWS AI and ML capabilities outside of AWS in a multicloud environment.

ML 99

ML Python Deep Learning Machine Learning 99

ODSC - Open Data Science

SEPTEMBER 21, 2023

Secondly, to be a successful ML engineer in the real world, you cannot just understand the technology; you must understand the business. Some typical examples are given in the following table, along with some discussion as to whether or not ML would be an appropriate tool for solving the problem: Figure 1.1:

Machine Learning 98

Machine Learning ML Engineer ML Data Science 98

Heartbeat

SEPTEMBER 18, 2023

Unleashing Innovation and Success: Comet — The Trusted ML Platform for Enterprise Environments Machine learning (ML) is a rapidly developing field, and businesses are increasingly depending on ML platforms to fuel innovation, improve efficiency, and mine data for insights.

ML 52

ML Data Scientist ML Engineer Machine Learning 52

Marktechpost

JANUARY 31, 2024

Data scientists and ML engineers often need help to build full-stack applications. These professionals typically have a firm grasp of data and AI algorithms. These solutions can be time-consuming and may not be feasible for data professionals who wish to focus primarily on their areas of expertise.

Data Scientist 134

Data Scientist Machine Learning Python ML Engineer 134

Towards AI

FEBRUARY 15, 2024

AI Engineers: Your Definitive Career Roadmap Become a professional certified AI engineer by enrolling in the best AI ML Engineer certifications that help you earn skills to get the highest-paying job. AI engineers usually work in an office environment as part of a team.

AI Engineer 94

AI Engineer Software Engineer Artificial Intelligence Artificial Intelligence 94

AWS Machine Learning Blog

FEBRUARY 27, 2024

In this post, we share how Axfood, a large Swedish food retailer, improved operations and scalability of their existing artificial intelligence (AI) and machine learning (ML) operations by prototyping in close collaboration with AWS experts and using Amazon SageMaker.

Machine Learning 112

Machine Learning DevOps Data Quality Data Scientist 112

ODSC - Open Data Science

FEBRUARY 20, 2023

As newer fields emerge within data science and the research is still hard to grasp, sometimes it’s best to talk to the experts and pioneers of the field. If you’re totally new to machine learning and data science, then consider getting an ODSC East Mini-Bootcamp pass. Recently, we spoke with Michael I.

Data Science 96

Data Science Machine Learning ML Engineer Python 96

ODSC - Open Data Science

APRIL 18, 2023

Mini-Bootcamp and VIP Pass holders will have access to four live virtual sessions on data science fundamentals. Confirmed sessions include: An Introduction to Data Wrangling with SQL with Sheamus McGovern, Software Architect, Data Engineer, and AI expert Programming with Data: Python and Pandas with Daniel Gerlanc, Sr.

Data Science 98

Data Science Software Architect ML Engineer Machine Learning 98

Towards AI

AUGUST 25, 2023

As a reminder, I highly recommend that you refer to more than one resource (other than documentation) when learning ML, preferably a textbook geared toward your learning level (beginner/intermediate / advanced). In a nutshell, AI Engineering is the application of software engineering best practices to the field of AI.

Software Engineer 96

Software Engineer Machine Learning Neural Network Artificial Intelligence 96

ODSC - Open Data Science

FEBRUARY 22, 2024

Andre Franca | CTO | connectedFlow Join this session to demystify the world of Causal AI, with a focus on understanding cause-and-effect relationships within data to drive optimal decisions. By the end of this session, you’ll have a practical blueprint to efficiently harness feature stores within ML workflows.

Machine Learning 52

Machine Learning Data Science Python ML 52

ODSC - Open Data Science

DECEMBER 7, 2023

Data Science & AI News New Breakthrough by Google DeepMind Unveils New Materials According to a new research paper, Google’s DeepMind has discovered hundreds of thousands of new hypothetical material designs. Need some help convincing your manager to send you to ODSC East this April?

Explainable AI 98

Explainable AI Data Scientist Data Science Python 98

Pickl AI

APRIL 19, 2023

Different industries from education, healthcare to marketing, retail and ecommerce require Machine Learning Engineers. Job market will experience a rise of 13% by 2026 for ML Engineers Why is Machine Learning Important? Accordingly, an entry-level ML engineer will earn around 5.1 Consequently.

Machine Learning 52

Machine Learning ML Engineer Data Scientist ML 52

AWS Machine Learning Blog

DECEMBER 1, 2023

Launched in 2019, Amazon SageMaker Studio provides one place for all end-to-end machine learning (ML) workflows, from data preparation, building and experimentation, training, hosting, and monitoring. About the Authors Mair Hasco is an AI/ML Specialist for Amazon SageMaker Studio. Get started on SageMaker Studio here.

ML 96

ML Machine Learning DevOps Computer Vision 96

ODSC - Open Data Science

MARCH 27, 2023

Learn about the flow, difficulties, and tools for performing ML clustering at scale Ori Nakar | Principal Engineer, Threat Research | Imperva Given that there are billions of daily botnet attacks from millions of different IPs, the most difficult challenge of botnet detection is choosing the most relevant data.

Machine Learning 98

Machine Learning Data Ingestion Explainability ML 98

AWS Machine Learning Blog

NOVEMBER 16, 2023

Amazon SageMaker provides purpose-built tools for machine learning operations (MLOps) to help automate and standardize processes across the ML lifecycle. In this post, we describe how Philips partnered with AWS to develop AI ToolSuite—a scalable, secure, and compliant ML platform on SageMaker.

Data Scientist 89

Data Scientist ML Data Science Automation 89

ODSC - Open Data Science

JANUARY 10, 2024

Andre Franca | CTO | connectedFlow Explore the world of Causal AI for data science practitioners, with a focus on understanding cause-and-effect relationships within data to drive optimal decisions. No-Code and Low-Code AI: A Practical Project-Driven Approach to ML Gwendolyn D.

Large Language Models 52

Large Language Models LLM Deep Learning ML 52

AWS Machine Learning Blog

FEBRUARY 13, 2024

Amazon SageMaker Feature Store is a fully managed, purpose-built repository to store, share, and manage features for machine learning (ML) models. Features are inputs to ML models used during training and inference. SageMaker Feature Store now makes it effortless to share, discover, and access feature groups across AWS accounts.

ML 105

ML ML Engineer Machine Learning Data Scientist 105

Pickl AI

APRIL 5, 2023

ML forms the underlying platform for several new developments. Hence, it has also triggered the demand for ML experts. However, if you are new to the tech domain and want to learn Machine Learning for free, then in this blog, we will take you through the 3 best options to start your ML learning journey. Is ML Coding Hard?

Machine Learning 52

Machine Learning ML Engineer ML Data Scientist 52

Towards AI

AUGUST 24, 2023

Common mistakes and misconceptions about learning AI/ML Markus Spiske on Unsplash A common misconception of beginners is that they can learn AI/ML from a few tutorials that implement the latest algorithms, so I thought I would share some notes and advice on learning AI. Trying to code ML algorithms from scratch.

Software Engineer 92

Software Engineer Neural Network Algorithm AI Engineer 92

Analytics Vidhya

FEBRUARY 17, 2022

This article was published as a part of the Data Science Blogathon. Image designed by the author Introduction Guys! Before getting started, just […]. The post K-Fold Cross Validation Technique and its Essentials appeared first on Analytics Vidhya.

Data Science 318

Data Science ML Engineer ML Python 318

Snorkel AI

MAY 1, 2024

provides expert end-to-end services for machine learning and data analytics. phData Senior ML Engineer Ryan Gooch recently evaluated options to accelerate ML model deployment with Snorkel Flow and AWS SageMaker. The Snorkel Flow platform integrates natively with AWS to make this data available with a few clicks.

AI Developer 52

AI Developer AI Development Machine Learning AI 52

AWS Machine Learning Blog

APRIL 11, 2023

Developing web interfaces to interact with a machine learning (ML) model is a tedious task. With Streamlit , developing demo applications for your ML solution is easy. Streamlit is an open-source Python library that makes it easy to create and share web apps for ML and data science.

ML Engineer 73

ML Engineer ML Data Scientist Machine Learning 73

Pickl AI

JANUARY 30, 2023

Since the rise of Data Science, it has found several applications across different industrial domains. However, the programming languages that work at the core of Data Science play a significant role in it. Hence for an individual who wants to excel as a data scientist, learning Python is a must.

Python 97

Python DevOps Machine Learning Automation 97

AWS Machine Learning Blog

OCTOBER 20, 2023

Customers of every size and industry are innovating on AWS by infusing machine learning (ML) into their products and services. Recent developments in generative AI models have further sped up the need of ML adoption across industries.

ML 101

ML Data Scientist ML Engineer Data Science 101

AWS Machine Learning Blog

JANUARY 10, 2024

Specialist Data Engineering at Merck, and Prabakaran Mathaiyan, Sr. ML Engineer at Tiger Analytics. The large machine learning (ML) model development lifecycle requires a scalable model release process similar to that of software development. The input to the training pipeline is the features dataset.

ML 98

ML Machine Learning ETL Data Scientist 98

TheSequence

JANUARY 19, 2024

You probably don’t need ML engineers In the last two years, the technical sophistication needed to build with AI has dropped dramatically. ML engineers used to be crucial to AI projects because you needed to train custom models from scratch. At the same time, the capabilities of AI models have grown.

Prompt Engineer 59

Prompt Engineer Prompt Engineering Generative AI Large Language Models 59

Heartbeat

OCTOBER 23, 2023

Revolutionizing Healthcare through Data Science and Machine Learning Image by Cai Fang on Unsplash Introduction In the digital transformation era, healthcare is experiencing a paradigm shift driven by integrating data science, machine learning, and information technology.

Data Scientist 52

Data Scientist Machine Learning Big Data Algorithm 52

Mlearning.ai

FEBRUARY 9, 2023

11 key differences in 2023 Photo by Jan Tinneberg on Unsplash Working in Data Science and Machine Learning (ML) professions can be a lot different from the expectation of it. A popular focus of a majority of Data Science courses, degrees, and online competitions is on creating a model that has the highest accuracy or best fit.

Data Scientist 52

Data Scientist Data Science ML Machine Learning 52

Mlearning.ai

MAY 23, 2023

Product First versus Model First mindset is a important concept as you mature in data science. It’s critical for beginners learn this, since it affects everything: workflows, data quality requirements, etc. Model mindset prioritizes the ML model that you are building. What is the Difference? Each has its place.

Machine Learning 52

Machine Learning Data Scientist ML Data Science 52

Heartbeat

FEBRUARY 1, 2023

Machine learning has become an essential part of our lives because we interact with various applications of ML models, whether consciously or unconsciously. Machine Learning Operations (MLOps) are the aspects of ML that deal with the creation and advancement of these models. What is MLOps?

DevOps 96

DevOps Machine Learning Data Scientist Software Engineer 96