Data Science Dojo

AUGUST 27, 2024

Algorithms: Decision trees, random forests, logistic regression, and more are like different techniques a detective might use to solve a case. Algorithms: Decision trees, random forests, logistic regression, and more are like different techniques a detective might use to solve a case.

Data Scientist 274

Data Scientist Data Science Machine Learning Machine Learning 274

Data Science Dojo

JUNE 1, 2023

The course covers topics such as linear regression, logistic regression, and decision trees. Machine Learning for Natural Language Processing by Christopher Manning, Jurafsky and Schütze This is an advanced-level course that teaches you how to use machine learning for natural language processing tasks.

Machine Learning 195

Machine Learning Machine Learning Natural Language Processing Deep Learning 195

Data Science Dojo

MAY 27, 2024

A visual representation of generative AI – Source: Analytics Vidhya Generative AI is a growing area in machine learning, involving algorithms that create new content on their own. These algorithms use existing data like text, images, and audio to generate content that looks like it comes from the real world.

K-nearest Neighbors 338

K-nearest Neighbors AI AI Supervised Learning 338

Pickl AI

SEPTEMBER 7, 2023

When you start exploring more about Machine Learning, you will come across the Gradient Boosting Algorithm. Basically, it is a powerful and versatile machine-learning algorithm that falls under the category of ensemble learning. Machine Learning models can leave you spellbound by their efficiency and proficiency.

Algorithm 52

Algorithm Decision Trees Machine Learning Machine Learning 52

Data Science Dojo

AUGUST 27, 2024

Algorithms: Decision trees, random forests, logistic regression, and more are like different techniques a detective might use to solve a case. Algorithms: Decision trees, random forests, logistic regression, and more are like different techniques a detective might use to solve a case.

Data Scientist 195

Data Scientist Data Science Machine Learning Machine Learning 195

Data Science Dojo

AUGUST 19, 2024

Business Benefits: Organizations are recognizing the value of AI and data science in improving decision-making, enhancing customer experiences, and gaining a competitive edge An AI research scientist acts as a visionary, bridging the gap between human intelligence and machine capabilities. Privacy: Protecting user privacy and data security.

AI 195

AI AI Machine Learning Machine Learning 195

Dataconomy

JULY 18, 2023

By leveraging artificial intelligence algorithms and data analytics, manufacturers can streamline their quoting process, improve accuracy, and gain a competitive edge in the market. This information helps businesses estimate the resources required and adjust pricing accordingly in real-time.

AI 91

AI AI Algorithm Predictive Analytics 91

Pickl AI

NOVEMBER 18, 2024

Key steps involve problem definition, data preparation, and algorithm selection. Basics of Machine Learning Machine Learning is a subset of Artificial Intelligence (AI) that allows systems to learn from data, improve from experience, and make predictions or decisions without being explicitly programmed.

Machine Learning 52

Machine Learning Machine Learning Decision Trees Algorithm 52

Pickl AI

JULY 12, 2024

Their interactive nature makes them suitable for experimenting with AI algorithms and analysing data. 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.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 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. 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. What is machine learning?

Machine Learning 97

Machine Learning Machine Learning Supervised Learning Clustering 97

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. What is Classification?

Clustering 52

Clustering Decision Trees Machine Learning Machine Learning 52

Pickl AI

AUGUST 1, 2023

Machine Learning models play a crucial role in this process, serving as the backbone for various applications, from image recognition to natural language processing. Examples of supervised learning models include linear regression, decision trees, support vector machines, and neural networks.

Machine Learning 52

Machine Learning Machine Learning Support Vector Machines Decision Trees 52

Towards AI

FEBRUARY 20, 2024

Beginner’s Guide to ML-001: Introducing the Wonderful World of Machine Learning: An Introduction Everyone is using mobile or web applications which are based on one or other machine learning algorithms. You might be using machine learning algorithms from everything you see on OTT or everything you shop online.

Machine Learning 81

Machine Learning Machine Learning ML ML 81

Heartbeat

OCTOBER 11, 2023

A key component of artificial intelligence is training algorithms to make predictions or judgments based on data. This process is known as machine learning or deep learning. In both cases, algorithms are trained to generate predictions or judgments based on data inputs. What is Machine Learning?

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Pickl AI

JANUARY 29, 2024

Data Science extracts insights, while Machine Learning focuses on self-learning algorithms. Key takeaways Data Science lays the groundwork for Machine Learning, providing curated datasets for ML algorithms to learn and make predictions. AI comprises Natural Language Processing, computer vision, and robotics.

Data Science 52

Data Science ML ML Machine Learning 52

Pickl AI

OCTOBER 24, 2024

Key Takeaways Scope and Purpose : Artificial Intelligence encompasses a broad range of technologies to mimic human intelligence, while Machine Learning focuses explicitly on algorithms that enable systems to learn from data. Supervised Learning : This is the most common form of ML, where algorithms learn from labelled data.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Machine Learning Machine Learning 52

Dataconomy

JUNE 13, 2023

Decision intelligence is an innovative approach that blends the realms of data analysis, artificial intelligence, and human judgment to empower businesses with actionable insights. Think of decision intelligence as a synergy between the human mind and cutting-edge algorithms. What is decision intelligence?

Power BI 103

Power BI Artificial Intelligence Artificial Intelligence Data Analysis 103

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. However, the process of creating AI can seem daunting to those who are unfamiliar with the technicalities involved. Train and evaluate the AI models for accuracy and efficiency.

Artificial Intelligence 98

Artificial Intelligence Artificial Intelligence Natural Language Processing Algorithm 98

ODSC - Open Data Science

AUGUST 15, 2023

You’ll get hands-on practice with unsupervised learning techniques, such as K-Means clustering, and classification algorithms like decision trees and random forest. Finally, you’ll explore how to handle missing values and training and validating your models using PySpark.

Machine Learning 52

Machine Learning Machine Learning Data Science Data Scientist 52

Dataconomy

AUGUST 31, 2023

Natural Language Processing (NLP) : Classification can be applied to text data to categorize messages, emails, or social media posts into different categories, such as spam vs. non-spam, positive vs. negative sentiment, or topic classification. Next, you need to select a model.

Machine Learning 136

Machine Learning Machine Learning Supervised Learning Algorithm 136

Pickl AI

SEPTEMBER 12, 2024

A Algorithm: A set of rules or instructions for solving a problem or performing a task, often used in data processing and analysis. 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.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Pickl AI

NOVEMBER 5, 2024

Data Science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data. AI encompasses various subfields, including Machine Learning (ML), Natural Language Processing (NLP), robotics, and computer vision.

Data Science 52

Data Science Artificial Intelligence Artificial Intelligence AI 52

Pickl AI

OCTOBER 18, 2023

Algorithms for Data Quality Enhancement Choosing the right algorithms and queries is imperative for companies dealing with extensive datasets. Random Forest: A Versatile Machine Learning Algorithm Random Forest is a flexible and widely machine-learning algorithm known for its simplicity and reliability.

Data Quality 52

Data Quality ML ML Machine Learning 52

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. You’ll see how these models can outperform counting-based methods by better-capturing language’s semantic subtleties and complexities.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Dataconomy

APRIL 4, 2023

Artificial Intelligence (AI) models are the building blocks of modern machine learning algorithms that enable machines to learn and perform complex tasks. These models are designed to replicate the human brain’s cognitive functions, enabling them to perceive, reason, learn, and make decisions based on data. What is an AI model?

K-nearest Neighbors 91

K-nearest Neighbors Decision Trees AI AI 91

Dataconomy

APRIL 4, 2023

Artificial Intelligence (AI) models are the building blocks of modern machine learning algorithms that enable machines to learn and perform complex tasks. These models are designed to replicate the human brain’s cognitive functions, enabling them to perceive, reason, learn, and make decisions based on data. What is an AI model?

K-nearest Neighbors 91

K-nearest Neighbors Decision Trees AI AI 91

Heartbeat

APRIL 17, 2023

Photo by Shahadat Rahman on Unsplash Introduction Machine learning (ML) focuses on developing algorithms and models that can learn from data and make predictions or decisions. One of the goals of ML is to enable computers to process and analyze data in a way that is similar to how humans process information. synonyms).

Natural Language Processing 52

Natural Language Processing Support Vector Machines Machine Learning Machine Learning 52

Dataconomy

MAY 25, 2023

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. This enables them to extract valuable insights, identify patterns, and make informed decisions in real-time.

Internet of Things 160

Internet of Things Artificial Intelligence Artificial Intelligence AI 160

Pickl AI

SEPTEMBER 30, 2024

Key concepts in ML are: Algorithms : Algorithms are the mathematical instructions that guide the learning process. They process data, identify patterns, and adjust the model accordingly. Common algorithms include decision trees, neural networks, and support vector machines.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Mlearning.ai

FEBRUARY 15, 2023

Introduction In natural language processing, text categorization tasks are common (NLP). Figure 4 Data Cleaning Conventional algorithms are often biased towards the dominant class, ignoring the data distribution. A random forest is an ensemble classifier that makes predictions using a variety of decision trees.

Cross Validation 52

Cross Validation Decision Trees Algorithm Natural Language Processing 52

Chatbots Life

SEPTEMBER 11, 2023

This limitation has paved the way for more advanced solutions that harness the power of Natural Language Processing (NLP). This has spurred the development of more advanced solutions powered by Natural Language Processing (NLP) that offer a more comprehensive approach to language-related tasks.

Natural Language Processing 59

Natural Language Processing Python ML ML 59

Pickl AI

AUGUST 23, 2023

By extracting insights from these datasets, professionals can make more informed investment decisions, reducing the risk associated with emotional biases. Through sophisticated algorithms and Machine Learning models , data scientists can predict stock price movements with a degree of accuracy that was previously unthinkable.

Data Science 52

Data Science Machine Learning Machine Learning Algorithm 52

IBM Journey to AI blog

JULY 6, 2023

Machine learning works on a known problem with tools and techniques, creating algorithms that let a machine learn from data through experience and with minimal human intervention. It processes enormous amounts of data a human wouldn’t be able to work through in a lifetime and evolves as more data is processed.

Machine Learning 80

Machine Learning Machine Learning Data Science Big Data 80

IBM Journey to AI blog

SEPTEMBER 5, 2023

However, more advanced chatbots can leverage artificial intelligence (AI) and natural language processing (NLP) to understand a user’s input and navigate complex human conversations with ease. Essentially, these chatbots operate like a decision tree.

Decision Trees 86

Decision Trees Artificial Intelligence Artificial Intelligence AI 86

Pickl AI

MAY 24, 2023

List of Python Libraries and Their Uses Given below are the Python Libraries that can be identified to be important working Python Libraries used by programmers in the industry: TensorFlow It is a computational library useful for writing new algorithms involving large number of tensor operations.

Data Science 52

Data Science Python Machine Learning Machine Learning 52

Pickl AI

NOVEMBER 8, 2023

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. Model Selection Picking the Right Algorithm Scikit-Learn boasts a variety of Machine Learning algorithms.

Machine Learning 52

Machine Learning Machine Learning Data Science Python 52

AssemblyAI

NOVEMBER 9, 2023

In Natural Language Processing (NLP), Text Summarization models automatically shorten documents, papers, podcasts, videos, and more into their most important soundbites. Taking this intuition further, we might consider the TextRank algorithm. The models are powered by advanced Deep Learning and Machine Learning research.

AI 102

AI AI Machine Learning Machine Learning 102