Data Science Dojo

JUNE 1, 2023

The course covers topics such as linear regression, logistic regression, and decision trees. Machine Learning for Absolute Beginners by Kirill Eremenko and Hadelin de Ponteves This is another beginner-level course that teaches you the basics of machine learning using Python.

Machine Learning 195

Machine Learning Machine Learning Natural Language Processing Deep Learning 195

IBM Journey to AI blog

DECEMBER 20, 2023

Machine learning types Machine learning algorithms fall into five broad categories: supervised learning, unsupervised learning, semi-supervised learning, self-supervised and reinforcement learning. the target or outcome variable is known). temperature, salary).

Machine Learning 92

Machine Learning Machine Learning Supervised Learning Clustering 92

Pickl AI

SEPTEMBER 16, 2024

Summary: This blog highlights ten crucial Machine Learning algorithms to know in 2024, including linear regression, decision trees, and reinforcement learning. Introduction Machine Learning (ML) has rapidly evolved over the past few years, becoming an integral part of various industries, from healthcare to finance.

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

Dataconomy

APRIL 4, 2023

Reminder : Training data refers to the data used to train an AI model, and commonly there are three techniques for it: Supervised learning: The AI model learns from labeled data, which means that each data point has a known output or target value. Let’s dig deeper and learn more about them!

K-nearest Neighbors 91

K-nearest Neighbors Decision Trees AI AI 91

Dataconomy

APRIL 4, 2023

Reminder : Training data refers to the data used to train an AI model, and commonly there are three techniques for it: Supervised learning: The AI model learns from labeled data, which means that each data point has a known output or target value. Let’s dig deeper and learn more about them!

K-nearest Neighbors 91

K-nearest Neighbors Decision Trees AI AI 91

AWS Machine Learning Blog

SEPTEMBER 10, 2024

The remaining features are horizontally appended to the pathology features, and a gradient boosted decision tree classifier (LightGBM) is applied to achieve predictive analysis. To further improve performance, a self-supervised learning-based approach, namely Hierarchical Image Pyramid Transformer (HIPT) ( Chen et al.,

Supervised Learning 92

Supervised Learning Machine Learning Machine Learning AWS 92

Smart Data Collective

JUNE 26, 2019

There are two essential classifiers for developing machine learning applications with this library: a supervised learning model known as an SVM and a Random Forest (RF). There are numerous reasons that scikit-learn is one of the preferred libraries for developing machine learning solutions.

Machine Learning 90

Machine Learning Machine Learning Python Decision Trees 90

Dataconomy

MAY 25, 2023

On the other hand, artificial intelligence focuses on creating intelligent systems that can learn, reason, and make decisions. When AI and IoT converge, we witness a synergy where AI empowers IoT devices with advanced analytics, automation, and intelligent decision-making.

Internet of Things 160

Internet of Things Artificial Intelligence Artificial Intelligence AI 160

Pickl AI

NOVEMBER 18, 2024

The main types are supervised, unsupervised, and reinforcement learning, each with its techniques and applications. Supervised Learning In Supervised Learning , the algorithm learns from labelled data, where the input data is paired with the correct output. spam email detection) and regression (e.g.,

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

Pickl AI

JULY 12, 2024

Machine Learning algorithms are trained on large amounts of data, and they can then use that data to make predictions or decisions about new data. There are three main types of Machine Learning: supervised learning, unsupervised learning, and reinforcement learning.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

IBM Journey to AI blog

JULY 6, 2023

Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. Ultimately, data science is used in defining new business problems that machine learning techniques and statistical analysis can then help solve. appeared first on IBM Blog.

Machine Learning 70

Machine Learning Machine Learning Data Science Big Data 70

Pickl AI

SEPTEMBER 12, 2024

Decision Trees: A supervised learning algorithm that creates a tree-like model of decisions and their possible consequences, used for both classification and regression tasks. Inductive Learning: A type of learning where a model generalises from specific examples to broader rules or patterns.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Mlearning.ai

NOVEMBER 29, 2023

Scientific studies forecasting  — Machine Learning and deep learning for time series forecasting accelerate the rates of polishing up and introducing scientific innovations dramatically. 19 Time Series Forecasting Machine Learning Methods How exactly does time series forecasting machine learning work in practice?

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

APRIL 26, 2024

Additionally, it delves into case study questions, advanced technical topics, and scenario-based queries, highlighting the skills and knowledge required for success in data analytics roles. Additionally, we’ve got your back if you consider enrolling in the best data analytics courses.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Pickl AI

AUGUST 9, 2024

It also addresses security, privacy concerns, and real-world applications across various industries, preparing students for careers in data analytics and fostering a deep understanding of Big Data’s impact. Velocity It indicates the speed at which data is generated and processed, necessitating real-time analytics capabilities.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

MAY 31, 2023

Accordingly, there are many Python libraries which are open-source including Data Manipulation, Data Visualisation, Machine Learning, Natural Language Processing , Statistics and Mathematics. Explore Machine Learning with Python: Become familiar with prominent Python artificial intelligence libraries such as sci-kit-learn and TensorFlow.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

Pickl AI

NOVEMBER 28, 2024

These techniques span different types of learning and provide powerful tools to solve complex real-world problems. Supervised Learning Supervised learning is one of the most common types of Machine Learning, where the algorithm is trained using labelled data.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

OCTOBER 24, 2024

Different ML types address various challenges, allowing machines to learn and adapt in diverse ways. Supervised Learning : This is the most common form of ML, where algorithms learn from labelled data. Machine Learning, on the other hand, focuses on task-specific learning.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Machine Learning Machine Learning 52

Pickl AI

SEPTEMBER 23, 2024

Healthcare Data Science is revolutionising healthcare through predictive analytics, personalised medicine, and disease detection. Data Science continues to impact various industries, driving innovation and efficiency through data-driven insights and advanced analytics.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Data Science Machine Learning 52

Dataconomy

FEBRUARY 26, 2025

This capability bridges various disciplines, leveraging techniques from statistics, machine learning, and artificial intelligence. Some key areas include: Big Data analytics: It helps in interpreting vast amounts of data to extract meaningful insights.

Support Vector Machines 91

Support Vector Machines Machine Learning Machine Learning Decision Trees 91

Dataconomy

MARCH 20, 2025

It acts as a learning mechanism, continuously refining model predictions through a process that adjusts weights based on errors. This iterative enhancement is vital for applications in predictive analytics, from face and speech recognition systems to complex natural language processing tasks. What is backpropagation?

Predictive Analytics 91

Predictive Analytics Machine Learning Machine Learning Deep Learning 91

How to Learn Machine Learning

MARCH 25, 2025

It plays a crucial role in areas like customer segmentation, fraud detection, and predictive analytics. At the core of machine learning, two primary learning techniques drive these innovations. These are known as supervised learning and unsupervised learning.

Supervised Learning 59

Supervised Learning Machine Learning Machine Learning Algorithm 59

ML @ CMU

DECEMBER 2, 2024

They also show that using this heavy-row-based parameterization is necessary for achieving high accuracy and improve on prior methods by reducing the gap requirement for random-order streams, though their method assumes the rows are presented in a random order rather than any order.

Deep Learning 230

Deep Learning Deep Learning Machine Learning Machine Learning 230