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. What is required to build an AI system?

Artificial Intelligence 98

Artificial Intelligence Artificial Intelligence Natural Language Processing Algorithm 98

How to Learn Machine Learning

DECEMBER 15, 2024

This professional certificate provides a holistic approach to machine learning, combining theoretical knowledge with practical skills.

Machine Learning 52

Machine Learning Machine Learning Deep Learning Deep Learning 52

Pickl AI

JANUARY 29, 2024

AI comprises Natural Language Processing, computer vision, and robotics. ML focuses on algorithms like decision trees, neural networks, and support vector machines for pattern recognition. Skills Proficiency in programming languages (Python, R), statistical analysis, and domain expertise are crucial.

Data Science 52

Data Science ML ML Machine Learning 52

Dataconomy

APRIL 4, 2023

Some of the common types are: Linear Regression Deep Neural Networks Logistic Regression Decision Trees AI Linear Discriminant Analysis Naive Bayes Support Vector Machines Learning Vector Quantization K-nearest Neighbors Random Forest What do they mean? It can work on any operating system that supports Cuda kernels.

K-nearest Neighbors 91

K-nearest Neighbors Decision Trees AI AI 91

Dataconomy

APRIL 4, 2023

Some of the common types are: Linear Regression Deep Neural Networks Logistic Regression Decision Trees AI Linear Discriminant Analysis Naive Bayes Support Vector Machines Learning Vector Quantization K-nearest Neighbors Random Forest What do they mean? It can work on any operating system that supports Cuda kernels.

K-nearest Neighbors 91

K-nearest Neighbors Decision Trees AI AI 91

Mlearning.ai

JULY 4, 2023

One such intriguing aspect is the potential to predict a user’s race based on their tweets, a task that merges the realms of Natural Language Processing (NLP), machine learning, and sociolinguistics.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Support Vector Machines 52

IBM Journey to AI blog

JULY 6, 2023

Today, machine learning has evolved to the point that engineers need to know applied mathematics, computer programming, statistical methods, probability concepts, data structure and other computer science fundamentals, and big data tools such as Hadoop and Hive. Python is the most common programming language used in machine learning.

Machine Learning 70

Machine Learning Machine Learning Data Science Big Data 70

Pickl AI

NOVEMBER 28, 2024

Summary: The blog discusses essential skills for Machine Learning Engineer, emphasising the importance of programming, mathematics, and algorithm knowledge. Key programming languages include Python and R, while mathematical concepts like linear algebra and calculus are crucial for model optimisation. during the forecast period.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

ODSC - Open Data Science

JANUARY 7, 2025

While knowing Python, R, and SQL is expected, youll need to go beyond that. Natural Language Processing (NLP) has emerged as a dominant area, with tasks like sentiment analysis, machine translation, and chatbot development leading the way. Employers arent just looking for people who can program.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

IBM Journey to AI blog

AUGUST 28, 2023

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. Machine learning algorithms like Naïve Bayes and support vector machines (SVM), and deep learning models like convolutional neural networks (CNN) are frequently used for text classification.

Machine Learning 68

Machine Learning Machine Learning Data Mining Data Mining 68

Pickl AI

SEPTEMBER 23, 2024

AI is making a difference in key areas, including automation, language processing, and robotics. Natural Language Processing: NLP helps machines understand and generate human language, enabling technologies like chatbots and translation.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Data Science Machine Learning 52

Heartbeat

MARCH 8, 2023

Source: Author Introduction Text classification, which involves categorizing text into specified groups based on its content, is an important natural language processing (NLP) task. R has a rich set of libraries and tools for machine learning and natural language processing, making it well-suited for spam detection tasks.

Machine Learning 52

Machine Learning Machine Learning Algorithm Data Mining 52

Pickl AI

SEPTEMBER 12, 2024

Joblib: A Python library used for lightweight pipelining in Python, handy for saving and loading large data structures. Normalisation: The process of scaling individual data points to a common range, often used to improve the performance of Machine Learning algorithms.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Pickl AI

NOVEMBER 18, 2024

Natural language processing ( NLP ) allows machines to understand, interpret, and generate human language, which powers applications like chatbots and voice assistants. These real-world applications demonstrate how Machine Learning is transforming technology. For instance: For a classification problem (e.g.,

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

DagsHub

DECEMBER 23, 2024

They are: Based on shallow, simple, and interpretable machine learning models like support vector machines (SVMs), decision trees, or k-nearest neighbors (kNN). We will divide this section into two  categories: Python library and web based tools. Libact : It is a Python package for active learning.

Deep Learning 52

Deep Learning Deep Learning Supervised Learning Clustering 52