ODSC - Open Data Science

JANUARY 7, 2025

The data science job market is rapidly evolving, reflecting shifts in technology and business needs. Heres what we noticed from analyzing this data, highlighting whats remained the same over the years, and what additions help make the modern data scientist in2025. Joking aside, this does infer particular skills.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

IBM Journey to AI blog

DECEMBER 19, 2023

As organizations collect larger data sets with potential insights into business activity, detecting anomalous data, or outliers in these data sets, is essential in discovering inefficiencies, rare events, the root cause of issues, or opportunities for operational improvements.

Machine Learning 82

Machine Learning Machine Learning Supervised Learning K-nearest Neighbors 82

Heartbeat

SEPTEMBER 28, 2023

. # Encode categorical features, scale numerical features encoder = OneHotEncoder(handle_unknown="ignore", sparse=False) scaler = StandardScaler() X_train, X_val, y_train, y_val = train_test_split(data.drop("Churn", axis=1), data["Churn"], test_size=0.2, These models serve as the basis for our ensemble approach.

Machine Learning 52

Machine Learning Machine Learning Support Vector Machines ML 52

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.

Machine Learning 52

Machine Learning Machine Learning Data Scientist Big Data Analytics 52

Heartbeat

MAY 22, 2023

Schematic diagram of the overall framework of Emotion Recognition System [ Source ] The models that are used for AI emotion recognition can be based on linear models like Support Vector Machines (SVMs) or non-linear models like Convolutional Neural Networks (CNNs). Thanks for reading!!

AI 52

AI AI Deep Learning Deep Learning 52

Pickl AI

MAY 10, 2023

Machine Learning is a subset of Artificial Intelligence and Computer Science that makes use of data and algorithms to imitate human learning and improving accuracy. Being an important component of Data Science, the use of statistical methods are crucial in training algorithms in order to make classification.

Clustering 52

Clustering Decision Trees Machine Learning Machine Learning 52

Heartbeat

APRIL 17, 2023

NRE is a complex task that involves multiple steps and requires sophisticated machine learning algorithms like Hidden Markov Models (HMMs) , Conditional Random Fields (CRFs), and Support Vector Machines (SVMs) be present. We’re committed to supporting and inspiring developers and engineers from all walks of life.

Natural Language Processing 52

Natural Language Processing Support Vector Machines Machine Learning Machine Learning 52

Ocean Protocol

JANUARY 10, 2024

This data challenge used carbon emission rates sorted by each country to prove or debunk common climate change assumptions with data science. Understanding trends of the past and simulating future outcomes through available data seeks to lead to better awareness, business intelligence, and policy shaping in years to come.

Data Science 52

Data Science Exploratory Data Analysis Support Vector Machines Data Analysis 52

Heartbeat

AUGUST 1, 2023

It is possible to improve the performance of these algorithms with machine learning algorithms such as Support Vector Machines. We’re committed to supporting and inspiring developers and engineers from all walks of life. Another advantage is that these algorithms are not limited to working independently.

Deep Learning 52

Deep Learning Deep Learning Algorithm Support Vector Machines 52

Heartbeat

OCTOBER 25, 2023

Bioinformatics: A Haven for Data Scientists and Machine Learning Engineers: Bioinformatics offers an unparalleled opportunity for data scientists and machine learning engineers to apply their expertise in solving complex biological problems.

Machine Learning 52

Machine Learning Machine Learning Data Scientist Algorithm 52

Heartbeat

MARCH 6, 2024

Editor's Note: Heartbeat is a contributor-driven online publication and community dedicated to providing premier educational resources for data science, machine learning, and deep learning practitioners. We're committed to supporting and inspiring developers and engineers from all walks of life.

Exploratory Data Analysis 52

Exploratory Data Analysis Support Vector Machines Data Analysis Data Analysis 52

Heartbeat

MARCH 21, 2023

Hinge Losses  — Another set of losses for classification problems, but commonly used in support vector machines. We’re committed to supporting and inspiring developers and engineers from all walks of life. Regression Losses  — When our predictions are going to be continuous.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Pickl AI

JULY 14, 2023

Machine Learning and Neural Networks (1990s-2000s): Machine Learning (ML) became a focal point, enabling systems to learn from data and improve performance without explicit programming. Techniques such as decision trees, support vector machines, and neural networks gained popularity.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence AI AI 52

Heartbeat

JUNE 14, 2023

Support vector machine classifiers as applied to AVIRIS data.” Cross Validated] Editor’s Note: Heartbeat is a contributor-driven online publication and community dedicated to providing premier educational resources for data science, machine learning, and deep learning practitioners. PMLR, 2017. [2]

Deep Learning 59

Deep Learning Deep Learning Support Vector Machines Machine Learning 59

Heartbeat

AUGUST 22, 2023

Its popularity is due to its relatively small size, simple and well-defined task, and high quality of the data. It has been used to train and test a variety of machine learning models, including artificial neural networks, convolutional neural networks, and support vector machines, among others.

Machine Learning 52

Machine Learning Machine Learning Natural Language Processing Support Vector Machines 52

Heartbeat

FEBRUARY 22, 2023

These features can then be used as input to another machine learning model, such as a support vector machine (SVM) or a random forest classifier, to perform tasks such as image classification or object detection. We’re committed to supporting and inspiring developers and engineers from all walks of life.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Heartbeat

OCTOBER 11, 2023

Model Complexity Machine Learning : Traditional machine learning models have fewer parameters and a simpler structure than deep learning models. They typically rely on simpler algorithms like decision trees, support vector machines, or linear regression.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Pickl AI

AUGUST 9, 2024

Data Streaming Learning about real-time data collection methods using tools like Apache Kafka and Amazon Kinesis. Students should understand the concepts of event-driven architecture and stream processing. Once data is collected, it needs to be stored efficiently.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Heartbeat

MARCH 8, 2023

The e1071 package provides a suite of statistical classification functions, including support vector machines (SVMs), which are commonly used for spam detection. Naive Bayes, according to Nagesh Singh Chauhan in KDnuggets, is a straightforward machine learning technique that uses Bayes’ theorem to create predictions.

Machine Learning 52

Machine Learning Machine Learning Algorithm Data Mining 52

Heartbeat

FEBRUARY 21, 2024

Hinge Loss (SVM Loss): Used for support vector machine (SVM) and binary classification problems. İrem KÖMÜRCÜ Editor's Note: Heartbeat is a contributor-driven online publication and community dedicated to providing premier educational resources for data science, machine learning, and deep learning practitioners.

Deep Learning 52

Deep Learning Deep Learning Algorithm Machine Learning 52

Pickl AI

OCTOBER 15, 2024

Predictive Models Predictive models are designed to forecast future outcomes based on historical data. They identify patterns in existing data and use them to predict unknown events. In more complex cases, you may need to explore non-linear models like decision trees, support vector machines, or time series models.

Decision Trees 52

Decision Trees Hypothesis Testing Clustering Data Analysis 52

Heartbeat

FEBRUARY 15, 2024

Classifier Integration: The HOG features are fed into a classifier, often a Support Vector Machine (SVM), which learns to distinguish between pedestrian and non-pedestrian patterns. We’re committed to supporting and inspiring developers and engineers from all walks of life. HOGDescriptor() hog.setSVMDetector(cv2.HOGDescriptor_getDefaultPeopleDetector())

Deep Learning 40

Deep Learning Deep Learning Support Vector Machines ML 40

PyImageSearch

SEPTEMBER 16, 2024

Anomaly detection ( Figure 2 ) is a critical technique in data analysis used to identify data points, events, or observations that deviate significantly from the norm. Supervised Learning These methods require labeled data to train the model. The model learns to distinguish between normal and abnormal data points.

Clustering 57

Clustering Algorithm Machine Learning Machine Learning 57

AWS Machine Learning Blog

FEBRUARY 5, 2024

According to health organizations such as the Centers for Disease Control and Prevention ( CDC ) and the World Health Organization ( WHO ), a spillover event at a wet market in Wuhan, China most likely caused the coronavirus disease 2019 (COVID-19). One of the models used is a support vector machine (SVM). min()) * 100).round(2)

ML 116

ML ML AWS Analytics 116