Data Science Dojo

AUGUST 27, 2024

They might find that it’s because of a popular deal or event on Tuesdays. Algorithms: Decision trees, random forests, logistic regression, and more are like different techniques a detective might use to solve a case. Imagine you’re trying to figure out why your favorite coffee shop is always busy on Tuesdays.

Data Scientist 195

Data Scientist Data Science Machine Learning Machine Learning 195

Pickl AI

JANUARY 2, 2025

Summary: Entropy in Machine Learning quantifies uncertainty, driving better decision-making in algorithms. It optimises decision trees, probabilistic models, clustering, and reinforcement learning. log2P(xi) measures the information content of each event in bits.

Machine Learning 52

Machine Learning Machine Learning Decision Trees Clustering 52

Pickl AI

MAY 10, 2023

Types of Classification: Logistic Regression It is the kind of Linear model that is used in the process of classification. In case you need to determine the likelihood of an event occurring, the application of sigmoid function is important. Consequently, each brand of the decision tree will yield a distinct result.

Clustering 52

Clustering Decision Trees Machine Learning Machine Learning 52

Pickl AI

SEPTEMBER 7, 2023

Gradient Boosting Iteratively builds weak learners, usually decision trees, by focusing on the residuals of the previous iteration’s predictions. Build a weak learner, usually a shallow decision tree, to understand and capture the patterns in the residuals. Weak Learner Creation: Address model shortcomings.

Algorithm 52

Algorithm Decision Trees Machine Learning Machine Learning 52

Dataconomy

MAY 25, 2023

Real-time decision-making With AI, IoT devices can make decisions in real-time based on the data they collect and analyze. This enables them to respond quickly to changing conditions or events. Unsupervised learning Unsupervised learning involves training machine learning models with unlabeled datasets.

Internet of Things 160

Internet of Things Artificial Intelligence Artificial Intelligence AI 160

ODSC - Open Data Science

SEPTEMBER 18, 2023

Getting started with natural language processing (NLP) is no exception, as you need to be savvy in machine learning, deep learning, language, and more. Interested in attending an ODSC event? Learn more about our upcoming events here. A lot goes into learning a new skill, regardless of how in-depth it is.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Heartbeat

OCTOBER 11, 2023

Deep learning is utilized in many fields, such as robotics, speech recognition, computer vision, and natural language processing. In many of these domains, it has cutting-edge performance and has made substantial advancements in areas like autonomous driving, speech and picture recognition, and language translation.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Heartbeat

APRIL 17, 2023

Named entity recognition (NER) is a subtask of natural language processing (NLP) that involves automatically identifying and classifying named entities mentioned in a text. SpaCy is a Python-based, open-source Natural Language Processing (NLP) library that was created to be quick, effective, and simple to use.

Natural Language Processing 52

Natural Language Processing Support Vector Machines Machine Learning Machine Learning 52

Cambridge Intelligence

FEBRUARY 20, 2024

FREE: Managing fraud The ultimate guide to fraud detection, investigation and prevention using data visualization GET YOUR FREE GUIDE The role of new & existing technology For many years, credit card companies have relied on analytics, algorithms and decision trees to power their fraud strategy. So where do humans fit into this?

AI 59

AI AI Machine Learning Machine Learning 59

Pickl AI

OCTOBER 18, 2023

It defines roles, responsibilities, and processes for data management. 6 Elements of Data Quality Accuracy Data accuracy measures how well the data reflects the real-world entities or events it represents. – Natural Language Processing (NLP) for text data standardization.

Data Quality 52

Data Quality ML ML Machine Learning 52

IBM Journey to AI blog

FEBRUARY 23, 2024

Beyond the simplistic chat bubble of conversational AI lies a complex blend of technologies, with natural language processing (NLP) taking center stage. ML and DL lie at the core of predictive analytics, enabling models to learn from data, identify patterns and make predictions about future events.

AI 116

AI AI ML ML 116

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. Joint Probability: The probability of two events co-occurring, often used in Bayesian statistics and probability theory.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Pickl AI

JULY 23, 2023

Diagnostic Analytics Diagnostic analytics goes further than descriptive analytics by focusing on why certain events occurred. Predictive analytics helps forecast potential scenarios and understand likely future events by analysing patterns and trends.

Analytics 52

Analytics Analytics Predictive Analytics Data Analysis 52

Heartbeat

FEBRUARY 22, 2023

These models have been used to achieve state-of-the-art performance in many different fields, including image classification, natural language processing, and speech recognition. The n_estimators argument is set to 100, meaning that 100 decision trees will be used in the forest.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Heartbeat

MAY 29, 2023

LLMs are one of the most exciting advancements in natural language processing (NLP). Part 1: Training LLMs Language models have become increasingly important in natural language processing (NLP) applications, and LLMs like GPT-3 have proven to be particularly successful in generating coherent and meaningful text.

Machine Learning 78

Machine Learning Machine Learning Natural Language Processing Data Preparation 78

ODSC - Open Data Science

JANUARY 7, 2025

Natural Language Processing (NLP) has emerged as a dominant area, with tasks like sentiment analysis, machine translation, and chatbot development leading the way. Neural networks form the core of deep learning applications, allowing for flexible, multi-layered learning processes.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

Pickl AI

AUGUST 23, 2023

Model Selection and Evaluation Experiment with different Machine Learning algorithms for stock price prediction, such as linear regression, decision trees , random forests, and neural networks. Natural Language Processing (NLP) algorithms process text data to determine whether news sentiment is positive, negative, or neutral.

Data Science 52

Data Science Machine Learning Machine Learning Algorithm 52

Pickl AI

JULY 14, 2023

Techniques such as decision trees, support vector machines, and neural networks gained popularity. Moreover, Deep Learning models, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), achieved remarkable breakthroughs in image classification, natural language processing, and other domains.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence AI AI 52

DagsHub

DECEMBER 23, 2024

Query Synthesis Scenario : Training a model to classify rare astronomical events using synthetic telescope data.   They are: Based on shallow, simple, and interpretable machine learning models like support vector machines (SVMs), decision trees, or k-nearest neighbors (kNN).

Deep Learning 52

Deep Learning Deep Learning Supervised Learning Clustering 52

Dataconomy

MARCH 28, 2025

Decision trees are a fundamental tool in machine learning, frequently used for both classification and regression tasks. Their intuitive, tree-like structure allows users to navigate complex datasets with ease, making them a popular choice for various applications in different sectors. What is a decision tree?

Decision Trees 91

Decision Trees Support Vector Machines Machine Learning Machine Learning 91

IBM Journey to AI blog

JUNE 5, 2024

If, for instance, a development team wants to understand which app features most significantly impact retention, it might use AI-driven natural language processing (NLP) to analyze unstructured data. AI technologies can also reveal and visualize data patterns to help with feature development. Predictive analytics.

Analytics 94

Analytics Analytics AI AI 94