How to Learn Machine Learning

DECEMBER 15, 2024

Course Highlights: Detailed exploration of supervised and unsupervised learning In-depth coverage of linear regression, logistic regression, and neural networks Advanced topics including support vector machines and anomaly detection Practical implementation using MATLAB/Octave Insights into machine learning best practices and optimization techniques (..)

Machine Learning 52

Machine Learning Machine Learning Deep Learning Deep Learning 52

Becoming Human

MARCH 16, 2023

These branches include supervised and unsupervised learning, as well as reinforcement learning, and within each, there are various algorithmic techniques that are used to achieve specific goals, such as linear regression, neural networks, and support vector machines.

AI 139

AI AI Deep Learning Deep Learning 139

IBM Journey to AI blog

JULY 6, 2023

That’s where data science comes in. The term data science was first used in the 1960s when it was interchangeable with the phrase “computer science.” ” “Data science” was first used as an independent discipline in 2001.

Machine Learning 70

Machine Learning Machine Learning Data Science Big Data 70

ODSC - Open Data Science

JANUARY 7, 2025

Just as a writer needs to know core skills like sentence structure and grammar, data scientists at all levels should know core data science skills like programming, computer science, algorithms, and soon. Theyre looking for people who know all related skills, and have studied computer science and software engineering.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

AWS Machine Learning Blog

FEBRUARY 25, 2025

Classification algorithms like support vector machines (SVMs) are especially well-suited to use this implicit geometry of the data. Diego Martn Montoro is an AI Expert and Machine Learning Engineer at Applus+ Idiada Datalab. This doesnt imply that clusters coudnt be highly separable in higher dimensions.

Algorithm 85

Algorithm Machine Learning Machine Learning K-nearest Neighbors 85

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

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. Requires a blend of computer science, mathematics, and domain-specific knowledge, often involving complex algorithms.

Data Science 52

Data Science ML ML Machine Learning 52

Pickl AI

JULY 12, 2024

Natural Language Processing (NLP) This is a field of computer science that deals with the interaction between computers and human language. NLP tasks include machine translation, speech recognition, and sentiment analysis. Popular models include decision trees, support vector machines (SVM), and neural networks.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Dataconomy

FEBRUARY 24, 2023

Several algorithms are available, including decision trees, neural networks, and support vector machines. The field of computer science known as “artificial intelligence” (AI) focuses on creating intelligent machines that can accomplish jobs that would normally need human intelligence.

Artificial Intelligence 91

Artificial Intelligence Artificial Intelligence AI AI 91

Heartbeat

OCTOBER 25, 2023

Empowering Data Scientists and Machine Learning Engineers in Advancing Biological Research Image from European Bioinformatics Institute Introduction: In biological research, the fusion of biology, computer science, and statistics has given birth to an exciting field called bioinformatics.

Machine Learning 52

Machine Learning Machine Learning Data Scientist Algorithm 52

Dataconomy

MARCH 13, 2023

How to create an artificial intelligence: Building accurate and efficient AI systems requires selecting the right algorithms and models that can perform the desired tasks effectively Developing AI Developing AI involves a series of steps that require expertise in several fields, such as data science, computer science, and engineering.

Artificial Intelligence 98

Artificial Intelligence Artificial Intelligence Natural Language Processing Algorithm 98

PyImageSearch

NOVEMBER 13, 2023

Step #3: Use transfer learning, specifically feature extraction, to compute features for each proposal (effectively an ROI) using the pre-trained CNN. Step #4: Classify each proposal using the extracted features with a Support Vector Machine (SVM). Or requires a degree in computer science?

Deep Learning 123

Deep Learning Deep Learning Algorithm Support Vector Machines 123

Pickl AI

SEPTEMBER 12, 2024

Artificial Intelligence (AI): A branch of computer science focused on creating systems that can perform tasks typically requiring human intelligence. Association Rule Learning: A rule-based Machine Learning method to discover interesting relationships between variables in large databases.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Pickl AI

SEPTEMBER 23, 2024

Understanding Data Science Data Science is a multidisciplinary field that uses scientific methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data. It combines principles from statistics, mathematics, computer science, and domain-specific knowledge to analyse and interpret complex data.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Data Science Machine Learning 52

PyImageSearch

JANUARY 2, 2023

Deep neural networks and support vector machines are being explored in developing pre-diabetic screening tools. Do you think learning computer vision and deep learning has to be time-consuming, overwhelming, and complicated? Or requires a degree in computer science? Diabetic Retinopathy, see Figure 9 ).

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

PyImageSearch

SEPTEMBER 16, 2024

For example, in fraud detection, SVM (support vector machine) can classify transactions as fraudulent or non-fraudulent based on historically labeled data. Do you think learning computer vision and deep learning has to be time-consuming, overwhelming, and complicated? Or requires a degree in computer science?

Clustering 57

Clustering Algorithm Machine Learning Machine Learning 57

DrivenData Labs

MAY 1, 2025

Some participants combined a transformer neural network with a tree-based model or support vector machine (SVM). I studied Computer Science and really enjoyed the AI space, although hardware resources were always limited, which shaped my push to always simplify.

Decision Trees 147

Decision Trees Clustering Algorithm Machine Learning 147

Flipboard

JULY 31, 2023

In their debut paper, they used a support-vector machine and only messed up 0.8% Do you think learning computer vision and deep learning has to be time-consuming, overwhelming, and complicated? Or requires a degree in computer science? of the time. Not too shabby, right? That’s not the case.

Machine Learning 123

Machine Learning Machine Learning Deep Learning Deep Learning 123