Dataconomy

MAY 25, 2023

On the other hand, artificial intelligence is the simulation of human intelligence in machines that are programmed to think and learn like humans. By leveraging advanced algorithms and machine learning techniques, IoT devices can analyze and interpret data in real-time, enabling them to make informed decisions and take autonomous actions.

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Internet of Things Artificial Intelligence Artificial Intelligence AI 160

Pickl AI

FEBRUARY 12, 2024

Technical Proficiency Data Science interviews typically evaluate candidates on a myriad of technical skills spanning programming languages, statistical analysis, Machine Learning algorithms, and data manipulation techniques. Differentiate between supervised and unsupervised learning algorithms.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Pickl AI

SEPTEMBER 3, 2023

Anomaly detection Machine Learning example: Given below are the Machine Learning anomaly detection examples that you need to know about: Network Intrusion Detection: Anomaly detection Machine Learning algorithms is used to monitor network traffic and identify unusual patterns that might indicate a cyberattack or unauthorised access.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Algorithm 52

Dataconomy

MARCH 13, 2023

With advances in machine learning, deep learning, and natural language processing, the possibilities of what we can create with AI are limitless. Key concepts of AI The following are some of the key concepts of AI: Data:  AI requires vast amounts of data to learn and improve its performance over time.

Artificial Intelligence 98

Artificial Intelligence Artificial Intelligence Natural Language Processing Algorithm 98

The MLOps Blog

DECEMBER 19, 2022

Traditional Machine Learning and Deep Learning methods are used to solve Multiclass Classification problems, but the model’s complexity increases as the number of classes increases. Particularly in Deep Learning, the network size increases as the number of classes increases. Let’s take a look at some of them.

ML 52

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Pickl AI

NOVEMBER 8, 2023

Versatility: From classification to regression, Scikit-Learn Cheat Sheet covers a wide range of Machine Learning tasks. Decision Tree) Making Predictions Evaluating Model Accuracy (Classification) Feature Scaling (Standardization) Getting Started Before diving into the intricacies of Scikit-Learn, let’s start with the basics.

Machine Learning 52

Machine Learning Machine Learning Data Science Python 52

Pickl AI

APRIL 26, 2024

Then, I would use clustering techniques such as k-means or hierarchical clustering to group customers based on similarities in their purchasing behaviour. Then, I would explore forecasting models such as ARIMA, exponential smoothing, or machine learning algorithms like random forests or gradient boosting to predict future sales.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

IBM Journey to AI blog

DECEMBER 20, 2023

Each type and sub-type of ML algorithm has unique benefits and capabilities that teams can leverage for different tasks. What is machine learning? Instead of using explicit instructions for performance optimization, ML models rely on algorithms and statistical models that deploy tasks based on data patterns and inferences.

Machine Learning 81

Machine Learning Machine Learning Supervised Learning Clustering 81

Towards AI

APRIL 4, 2024

Created by the author with DALL E-3 Machine learning algorithms are the “cool kids” of the tech industry; everyone is talking about them as if they were the newest, greatest meme. Amidst the hoopla, do people actually understand what machine learning is, or are they just using the word as a text thread equivalent of emoticons?

K-nearest Neighbors 70

K-nearest Neighbors Machine Learning Machine Learning Decision Trees 70

Mlearning.ai

MAY 23, 2023

An interdisciplinary field that constitutes various scientific processes, algorithms, tools, and machine learning techniques working to help find common patterns and gather sensible insights from the given raw input data using statistical and mathematical analysis is called Data Science. Decision trees are more prone to overfitting.

Data Science 52

Data Science Decision Trees Deep Learning Deep Learning 52

DagsHub

APRIL 21, 2024

Moving the machine learning models to production is tough, especially the larger deep learning models as it involves a lot of processes starting from data ingestion to deployment and monitoring. It provides different features for building as well as deploying various deep learning-based solutions. What is MLOps?

Machine Learning 59

Machine Learning Machine Learning ML ML 59

Data Science Dojo

AUGUST 30, 2023

It directly focuses on implementing scientific methods and algorithms to solve real-world business problems and is a key player in transforming raw data into significant and actionable business insights. Machine learning algorithms Machine learning forms the core of Applied Data Science.

Data Science 195

Data Science Hypothesis Testing Machine Learning Machine Learning 195

Iguazio

APRIL 24, 2024

Contextual Learning - With their deep learning architecture, LLMs can grasp the nuances of language, including idioms, cultural references and complex syntax. This is important for real-time decision-making tasks, like autonomous vehicles or high-frequency trading. High efficiency in specific, well-defined problem spaces.

ML 52

ML ML AI AI 52