Data Science Dojo

AUGUST 19, 2024

They dive deep into artificial neural networks, algorithms, and data structures, creating groundbreaking solutions for complex issues. These professionals venture into new frontiers like machine learning, natural language processing, and computer vision, continually pushing the limits of AI’s potential.

AI 357

AI AI Machine Learning Machine Learning 357

Smart Data Collective

JUNE 4, 2021

Data scientists use algorithms for creating data models. Programming Language (R or Python). Programmers can start with either R or Python. it is overwhelming to learn data science concepts and a general-purpose language like python at the same time. Python can be added to the skill set later.

Data Science 133

Data Science Exploratory Data Analysis Machine Learning Machine Learning 133

Data Science Dojo

JUNE 1, 2023

Machine Learning for Absolute Beginners by Kirill Eremenko and Hadelin de Ponteves This is another beginner-level course that teaches you the basics of machine learning using Python. The course covers topics such as supervised learning, unsupervised learning, and reinforcement learning.

Machine Learning 195

Machine Learning Machine Learning Natural Language Processing Deep Learning 195

Smart Data Collective

JUNE 26, 2019

Python is arguably the best programming language for machine learning. However, many aspiring machine learning developers don’t know where to start. They should look into the scikit-learn library, which is one of the best for developing machine learning applications. Decision boundary learning with SVMs.

Machine Learning 91

Machine Learning Machine Learning Python Decision Trees 91

Towards AI

APRIL 7, 2024

Created by the author with DALL E-3 Statistics, regression model, algorithm validation, Random Forest, K Nearest Neighbors and Naïve Bayes— what in God’s name do all these complicated concepts have to do with you as a simple GIS analyst? You just want to create and analyze simple maps not to learn algebra all over again.

Machine Learning 105

Machine Learning Machine Learning K-nearest Neighbors Supervised Learning 105

Towards AI

APRIL 10, 2024

Let us look at how the K Nearest Neighbor algorithm can be applied to geospatial analysis. A non-parametric, supervised learning classifier, the K-Nearest Neighbors (k-NN) algorithm uses proximity to classify or predict how a single data point will be grouped. What is K Nearest Neighbor?

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K-nearest Neighbors Algorithm Python Clustering 116

Pickl AI

FEBRUARY 2, 2025

Popular tools for implementing it include WEKA, RapidMiner, and Python libraries like mlxtend. Classification: How it Differs from Association Rules Classification is a supervised learning technique that aims to predict a target or class label based on input features. The rules are then applied for classification purposes.

Data Mining 52

Data Mining Data Mining Data Mining Decision Trees 52

IBM Journey to AI blog

DECEMBER 19, 2023

In this blog we’ll go over how machine learning techniques, powered by artificial intelligence, are leveraged to detect anomalous behavior through three different anomaly detection methods: supervised anomaly detection, unsupervised anomaly detection and semi-supervised anomaly detection.

Machine Learning 82

Machine Learning Machine Learning Supervised Learning K-nearest Neighbors 82

Pickl AI

JULY 12, 2024

Summary: This guide explores Artificial Intelligence Using Python, from essential libraries like NumPy and Pandas to advanced techniques in machine learning and deep learning. Python’s simplicity, versatility, and extensive library support make it the go-to language for AI development.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

AWS Machine Learning Blog

JULY 18, 2023

The built-in BlazingText algorithm offers optimized implementations of Word2vec and text classification algorithms. The BlazingText algorithm expects a single preprocessed text file with space-separated tokens. If you are prompted to choose a Kernel, choose the Python 3 (Data Science 3.0) kernel and choose Select.

Supervised Learning 85

Supervised Learning Algorithm Natural Language Processing AWS 85

Pickl AI

MARCH 13, 2023

INTRODUCTION Machine Learning is a subfield of artificial intelligence that focuses on the development of algorithms and models that allow computers to learn and make predictions or decisions based on data, without being explicitly programmed. and divides them as per the presence and absence of those similar patterns.

Clustering 52

Clustering Algorithm Machine Learning Machine Learning 52

Explosion

APRIL 1, 2017

Prodigy features many of the ideas and solutions for data collection and supervised learning outlined in this blog post. It’s a cloud-free, downloadable tool and comes with powerful active learning models. Sometimes the unsupervised algorithm will happen to produce the output you want, but other times it won’t.

Supervised Learning 40

Supervised Learning Machine Learning Machine Learning Algorithm 40

Towards AI

MAY 1, 2024

In this piece, we shall look at tips and tricks on how to perform particular GIS machine learning algorithms regardless of your expertise in GIS, if you are a fresh beginner with no experience or a seasoned expert in geospatial machine learning. Advantages of Using R for Machine Learning 1. Decision Tree and R.

Machine Learning 98

Machine Learning Machine Learning K-nearest Neighbors Decision Trees 98

AWS Machine Learning Blog

MAY 8, 2024

Amazon SageMaker JumpStart provides a suite of built-in algorithms , pre-trained models , and pre-built solution templates to help data scientists and machine learning (ML) practitioners get started on training and deploying ML models quickly. You can use these algorithms and models for both supervised and unsupervised learning.

Algorithm 112

Algorithm Machine Learning Machine Learning ML 112

Pickl AI

AUGUST 8, 2024

Summary: Support Vector Machine (SVM) is a supervised Machine Learning algorithm used for classification and regression tasks. Among the many algorithms, the SVM algorithm in Machine Learning stands out for its accuracy and effectiveness in classification tasks. What is the SVM Algorithm in Machine Learning?

Machine Learning 52

Machine Learning Machine Learning Algorithm Support Vector Machines 52

Pickl AI

MAY 31, 2023

Python is one of the widely used programming languages in the world having its own significance and benefits. Its efficacy may allow kids from a young age to learn Python and explore the field of Data Science. Some of the top Data Science courses for Kids with Python have been mentioned in this blog for you.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

Towards AI

JULY 22, 2023

The math behind the Logistic Regression algorithm and implementation from scratch using Numpy. Image by Author Introduction Logistic Regression is a fundamental binary classification algorithm that can learn a decision boundary between two different sets of data attributes. The class labels, denoted by y, are either 0 or 1.

Algorithm 98

Algorithm Supervised Learning Python AI 98

ODSC - Open Data Science

JULY 26, 2023

Machine learning is a subfield of artificial intelligence (AI) that enables computers to learn and make decisions or predictions without explicit programming. It involves feeding data to algorithms, which then generalize patterns and make inferences about unseen data. Common supervised learning tasks include classification (e.g.,

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

AUGUST 1, 2023

In this article, we will explore the concept of applied text mining in Python and how to do text mining in Python. Introduction to Applied Text Mining in Python Before going ahead, it is important to understand, What is Text Mining in Python? How To Do Text Mining in Python?

Data Analysis 52

Data Analysis Data Analysis Python Support Vector Machines 52

BAIR

APRIL 6, 2023

The closest analogue in academia is interactive imitation learning (IIL) , a paradigm in which a robot intermittently cedes control to a human supervisor and learns from these interventions over time. Using this formalism, we can now instantiate and compare IFL algorithms (i.e., allocation policies) in a principled way.

Algorithm 98

Algorithm Artificial Intelligence Artificial Intelligence Supervised Learning 98

Becoming Human

MAY 15, 2023

One is a scripting language such as Python, and the other is a Query language like SQL (Structured Query Language) for SQL Databases. Python is a High-level, Procedural, and object-oriented language; it is also a vast language itself, and covering the whole of Python is one the worst mistakes we can make in the data science journey.

Data Science 75

Data Science Machine Learning Machine Learning Database 75

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

Dataconomy

MARCH 13, 2023

Key concepts of AI The following are some of the key concepts of AI: Data:  AI requires vast amounts of data to learn and improve its performance over time. Algorithms:  AI algorithms are used to process the data and extract insights from it. Develop AI models using machine learning or deep learning algorithms.

Artificial Intelligence 98

Artificial Intelligence Artificial Intelligence Natural Language Processing Algorithm 98

AWS Machine Learning Blog

NOVEMBER 10, 2023

We previously explored a single job optimization, visualized the outcomes for SageMaker built-in algorithm, and learned about the impact of particular hyperparameter values. In this post, we run multiple HPO jobs with a custom training algorithm and different HPO strategies such as Bayesian optimization and random search.

ML 104

ML ML Algorithm Python 104

Towards AI

FEBRUARY 19, 2025

Unlike traditional software programs, AI agents use machine learning models to adapt their behavior based on data. Decision-Making: Algorithms to process inputs and decide on actions. Learning: Ability to improve performance over time using feedback loops. Unsupervised Learning: Finding hidden structures in unlabeled data.

Natural Language Processing 54

Natural Language Processing Machine Learning Machine Learning AI 54

Pickl AI

NOVEMBER 18, 2024

Key Takeaways Machine Learning Models are vital for modern technology applications. Types include supervised, unsupervised, and reinforcement learning. Key steps involve problem definition, data preparation, and algorithm selection. Ethical considerations are crucial in developing fair Machine Learning solutions.

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

ODSC - Open Data Science

OCTOBER 2, 2023

c is written in C, while the original LLM is written in Python. Some of the languages include Python, Java, and C++. It can also be used to generate code for specific purposes, such as generating code to implement a specific algorithm or to generate code to solve a specific problem. This makes LLama2.c

Data Science 98

Data Science Supervised Learning Python AI 98

How to Learn Machine Learning

MAY 14, 2023

Mathematics is crucial because machine learning algorithms are built on concepts such as linear algebra, calculus, probability, and statistics. Familiarity with these subjects will enable you to understand and implement machine learning algorithms more effectively.

Machine Learning 52

Machine Learning Machine Learning Deep Learning Deep Learning 52

AWS Machine Learning Blog

NOVEMBER 27, 2023

While this data holds valuable insights, its unstructured nature makes it difficult for AI algorithms to interpret and learn from it. As AI adoption continues to accelerate, developing efficient mechanisms for digesting and learning from unstructured data becomes even more critical in the future. And select Python (PySpark).

Data Preparation 86

Data Preparation AI AI Python 86

Pickl AI

OCTOBER 20, 2024

Summary: Learning Artificial Intelligence involves mastering Python programming, understanding Machine Learning principles, and engaging in practical projects. This guide will help beginners understand how to learn Artificial Intelligence from scratch. For example, You can learn Python on Pickl.AI

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Machine Learning Machine Learning 52

Mlearning.ai

SEPTEMBER 24, 2023

A brute-force search is a general problem-solving technique and algorithm paradigm. Maximum Time by the algorithm The running time complexity (Big O notation) is different for different algorithms. Big O notation is a mathematical concept to describe the complexity of algorithms. 2019) Data Science with Python.

Cross Validation 52

Cross Validation Algorithm Supervised Learning Python 52

Pickl AI

DECEMBER 17, 2024

Summary: Stochastic Gradient Descent (SGD) is a foundational optimisation algorithm in Machine Learning. It efficiently handles large datasets, adapts through advanced variants, and powers applications in Deep Learning frameworks. Optimisation is crucial in Machine Learning, ensuring efficient learning and better generalisation.

Machine Learning 52

Machine Learning Machine Learning Deep Learning Deep Learning 52

Pickl AI

JULY 10, 2024

Understanding AI and Machine Learning Artificial Intelligence (AI) is the simulation of human intelligence in machines designed to think and act like humans. AI encompasses various technologies and applications, from simple algorithms to complex neural networks. Key Features: Comprehensive coverage of Machine Learning models.

Machine Learning 52

Machine Learning Machine Learning Deep Learning Deep Learning 52

Pickl AI

FEBRUARY 12, 2024

Technical Proficiency Data Science interviews typically evaluate candidates on a myriad of technical skills spanning programming languages, statistical analysis, Machine Learning algorithms, and data manipulation techniques. Differentiate between supervised and unsupervised learning algorithms.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Explosion

AUGUST 3, 2017

In order to take full advantage of this strategy, Prodigy is provided as a Python library and command line utility, with a flexible web application. The components are wired togther into a recipe , by adding the @recipe decorator to any Python function. Recipes can start the web service by return a dictionary of components.

Supervised Learning 52

Supervised Learning Python Machine Learning Machine Learning 52

IBM Journey to AI blog

JUNE 14, 2023

With a foundation model, often using a kind of neural network called a “transformer” and leveraging a technique called self-supervised learning, you can create pre-trained models for a vast amount of unlabeled data. It becomes difficult to ensure that the model algorithms outputs aren’t biased, or even toxic.

AI 103

AI AI Natural Language Processing Data Lakes 103

IBM Journey to AI blog

JULY 6, 2023

Just as humans can learn through experience rather than merely following instructions, machines can learn by applying tools to data analysis. 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.

Machine Learning 70

Machine Learning Machine Learning Data Science Big Data 70