Data Science Dojo

SEPTEMBER 8, 2023

Their expertise in deciphering data patterns is indispensable in making accurate forecasts. Machine Learning and Deep Learning: The Power Duo Machine Learning (ML) and Deep Learning (DL) are two critical branches of AI that bring exceptional capabilities to predictive analytics. Goals To predict future events and trends.

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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. Scikit Learn Scikit Learn is a comprehensive machine learning tool designed for data mining and large-scale unstructured data analysis.

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Machine Learning Machine Learning ML ML 98

Dataconomy

JULY 4, 2023

Hyper automation, which uses cutting-edge technologies like AI and ML, can help you automate even the most complex tasks. It’s also about using AI and ML to gain insights into your data and make better decisions. ML algorithms enable systems to identify patterns, make predictions, and take autonomous actions.

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Data Science Dojo

JANUARY 20, 2023

These tutorials include topics like R & Python programming , data mining , and Azure ML (Machine Learning). Our in-person bootcamp cuts through the fluff so that you’re applying concepts and techniques back at work in only five days, rather than weeks, without sacrificing any limbs.

Data Science 195

Data Science Natural Language Processing Data Mining Data Mining 195

ODSC - Open Data Science

FEBRUARY 10, 2023

Faster Training and Inference Using the Azure Container for PyTorch in Azure ML If you’ve ever wished that you could speed up the training of a large PyTorch model, then this post is for you. In this post, we’ll cover the basics of this new environment, and we’ll show you how you can use it within your Azure ML project.

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Smart Data Collective

DECEMBER 19, 2021

Besides, it offers data model creation, systematized data sets, developable web services, ML-powered algorithms, versatile use of data mining and so many other very efficient functionalities that make it very flexible and productive to use for Data Preprocessing.

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Python Machine Learning Machine Learning Algorithm 141

Flipboard

FEBRUARY 11, 2025

Science & Society Athina Samara Prompted by the recently proposed conceptual redefinition of biocompatibility for machine learning (ML) and data-mining

Data Mining 50

Data Mining Data Mining Data Mining Machine Learning 50

Towards AI

JANUARY 6, 2025

Natural language processing, computer vision, data mining, robotics, and other competencies are strengthened in the course. However, you are expected to possess intermediate coding experience and a background as an AI ML engineer; to begin with the course. Generative AI with LLMs course by AWS AND DEEPLEARNING.AI

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Data Science Dojo

FEBRUARY 2, 2023

To build a chatbot using Python, you will need to use a combination of NLP and ML techniques. Web Scraper Web scraping is the process of extracting data from websites and a web scraper is a tool that automates this process. To build a web scraper, you will first need to install the Beautiful Soup library and the requests library.

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Python Data Analysis Data Analysis Data Science 195

Pickl AI

JANUARY 23, 2023

It is not a good when dealing with RNN (Recurrent Neural Networks) Also See: 5 Machine Learning Algorithms That Every ML Engineer Should know Microsoft CNTK CNTK is a deep learning framework that was created by Microsoft Research. 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

Towards AI

AUGUST 25, 2023

Many Discord users are high school and undergraduate college students with no AI/ML or software engineering experience. The first step in solving an AI/ML problem is to be able to describe and understand the problem in detail. Describe the problem, including the category of ML problem. Describe any models that you have tried.

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Becoming Human

JANUARY 23, 2023

After understanding data science let’s discuss the second concern “ Data Science vs AI ”. So, we know that data science is a process of getting insights from data and helps the business but where this Artificial Intelligence (AI) lies? So, it looks like magic but it’s not magic. If we talk about AI.

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Data Science Big Data Big Data Deep Learning 105

Towards AI

FEBRUARY 1, 2024

If you are passionate about AI/ML and looking for a teammate to explore, contact them in the thread! If you are passionate about working in AI and have the technical skills and passion for these roles, connect with them in the thread! Algorithms autonomously find groupings, and metrics like the Dunn index assess their precision.

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Smart Data Collective

APRIL 8, 2020

This data is then processed, transformed, and consumed to make it easier for users to access it through SQL clients, spreadsheets and Business Intelligence tools. Data warehousing also facilitates easier data mining, which is the identification of patterns within the data which can then be used to drive higher profits and sales.

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AWS Machine Learning Blog

JANUARY 13, 2023

Although the volume of HCLS-generated data has never been greater, the challenges and constraints associated with accessing such data limits its utility for future research. We have developed an FL framework on AWS that enables analyzing distributed and sensitive health data in a privacy-preserving manner.

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IBM Journey to AI blog

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. What is MLOps?

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IBM Journey to AI blog

AUGUST 14, 2023

The newly launched IBM Security QRadar Suite offers AI, machine learning (ML) and automation capabilities across its integrated threat detection and response portfolio , which includes EDR , log management and observability, SIEM and SOAR. Let’s take a closer look at QRadar EDR and QRadar SIEM to show how AI, ML and automation are used.

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Dataconomy

NOVEMBER 29, 2022

In the modern world, obtaining data is easier than ever, but generating insights and information from that data is becoming more challenging. Businesses regularly find themselves in a situation where they have far more data than they know what to do with, which may be counterproductive and lead to inaction.

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AWS Machine Learning Blog

JUNE 26, 2024

This blog is part of the series, Generative AI and AI/ML in Capital Markets and Financial Services. They face many challenges because of the increasing variety of tools and amount of data. Sovik Kumar Nath is an AI/ML and GenAI specialist senior solution architect with AWS working with financial services and capital markets customers.

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AWS AI AI Database 121

DagsHub

APRIL 21, 2024

A traditional machine learning (ML) pipeline is a collection of various stages that include data collection, data preparation, model training and evaluation, hyperparameter tuning (if needed), model deployment and scaling, monitoring, security and compliance, and CI/CD. What is MLOps?

Machine Learning 59

Machine Learning Machine Learning ML ML 59

phData

FEBRUARY 7, 2024

On the client side, Snowpark consists of libraries, including the DataFrame API and native Snowpark machine learning (ML) APIs for model development (public preview) and deployment (private preview). Machine Learning Training machine learning (ML) models can sometimes be resource-intensive.

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IBM Journey to AI blog

JULY 6, 2023

Data science solves a business problem by understanding the problem, knowing the data that’s required, and analyzing the data to help solve the real-world problem. Machine learning (ML) is a subset of artificial intelligence (AI) that focuses on learning from what the data science comes up with.

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Machine Learning Machine Learning Data Science Big Data 70

IBM Journey to AI blog

APRIL 15, 2024

Virtualization layer abstraction and developer benefits Advantage: The virtualization layer in the data platform acts as an abstraction layer. They can focus on designing the core logic of their models without getting bogged down in data management complexities.

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Analytics Analytics Data Silos AI 81

IBM Journey to AI blog

MARCH 14, 2024

Try Db2 Warehouse SaaS on AWS for free   Netezza SaaS on AWS IBM® Netezza® Performance Server is a cloud-native data warehouse designed to operationalize deep analytics, data mining and BI by unifying, accessing and scaling all types of data across the hybrid cloud. Netezza

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Pickl AI

MAY 30, 2023

Moreover, you can easily opt for 6 month certification program that pays well in the field that will allow you to gain perfection in ML. Learn the techniques in Machine Learning Use different tools for applications of ML and NLP Salary of the ML Engineer in India ranges between 3 Lakhs to 20.8 Lakhs annually.

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Data Science Data Mining Data Mining Data Mining 52

AWS Machine Learning Blog

SEPTEMBER 19, 2023

He helps startups with their cloud journey, and is passionate about containers and ML. Dmitry Zadorozhny is a data analyst at virtuswap.io. He is responsible for data mining, processing and storage, as well as integrating cloud services such as AWS. Omer Haim is a Senior Startup Solutions Architect at Amazon Web Services.

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AWS Data Science Data Mining Data Mining 134

Pickl AI

NOVEMBER 4, 2024

Use cases include visualising distributions, relationships, and categorical data, effortlessly enhancing the aesthetics of your plots. It offers simple and efficient tools for data mining and Data Analysis. Scikit-learn Scikit-learn is the go-to library for Machine Learning in Python.

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Data Science Python Machine Learning Machine Learning 52

Pickl AI

SEPTEMBER 23, 2024

Machine Learning Machine Learning (ML) is a crucial component of Data Science. It enables computers to learn from data without explicit programming. ML models help predict outcomes, automate tasks, and improve decision-making by identifying patterns in large datasets.

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Artificial Intelligence Artificial Intelligence Data Science Machine Learning 52

Defined.ai blog

AUGUST 30, 2023

At its core, NLP in machine learning (ML) is where the intricate art of language meets the precision of algorithms. It’s akin to teaching machines to not merely recognize words but to respond to them in ways that mimic human understanding, forging connections that transcend mere data processing.

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Machine Learning Machine Learning Natural Language Processing ML 52

Pickl AI

JUNE 7, 2023

It requires you to combine historical usage patterns with weather data for predicting the demand of rental services. The primary goal of the Kaggle competition is creating an ML Model that can predict the total number of bikes rented. You will need to use the K-clustering method for this GitHub data mining project.

Data Science 52

Data Science Deep Learning Deep Learning Clustering 52

Towards AI

JULY 17, 2023

Apriori Machine Learning Algorithm, Explained A powerful yet simple ML algorithm for generating recommendations medium.com Image Source: [link] Purpose We started the study with the intent of finding some out-of-the-box association rules. If not, we suggest you take a look at the following quick 7-minute article by Eliana Grosof.

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Algorithm Machine Learning Machine Learning AI 98

IBM Journey to AI blog

AUGUST 28, 2023

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. What is text mining? Text analysis takes it a step farther by focusing on pattern identification across large datasets, producing more quantitative results.

Machine Learning 68

Machine Learning Machine Learning Data Mining Data Mining 68

ODSC - Open Data Science

MAY 1, 2023

Pedro Domingos, PhD Professor Emeritus, University Of Washington | Co-founder of the International Machine Learning Society Pedro Domingos is a winner of the SIGKDD Innovation Award and the IJCAI John McCarthy Award, two of the highest honors in data science and AI. Audrey Reznik Guidera Sr.

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Heartbeat

OCTOBER 23, 2023

The Role of Data Scientists and ML Engineers in Health Informatics At the heart of the Age of Health Informatics are data scientists and ML engineers who play a critical role in harnessing the power of data and developing intelligent algorithms. We pay our contributors, and we don't sell ads.

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Machine Learning Machine Learning Data Scientist Big Data Analytics 52

Becoming Human

MAY 9, 2024

It’s crucial in various AI and machine learning (ML) applications. In AI, entities refer to tangible and intangible elements like people, organizations, locations, and dates embedded in text data. Data Mining : NER is used to identify key entities in large datasets, extracting valuable insights.

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Pickl AI

MAY 10, 2023

Being an important component of Data Science, the use of statistical methods are crucial in training algorithms in order to make classification. Certainly, these predictions and classification help in uncovering valuable insights in data mining projects.

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Clustering Decision Trees Machine Learning Machine Learning 52

Heartbeat

MARCH 8, 2023

Because of the package’s emphasis on tidy data, it is both a user-friendly option for those new to text analysis, and a valuable tool for experienced practitioners. Data mining, text classification, and information retrieval are just a few applications. References Nagesh, Singh Chauhan.

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