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

Towards AI

FEBRUARY 13, 2024

Louis-François Bouchard in What is Artificial Intelligence Introduction to self-supervised learning·4 min read·May 27, 2020 80 … Read the full blog for free on Medium. Join thousands of data leaders on the AI newsletter. Author(s): Louis-François Bouchard Originally published on Towards AI.

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Pickl AI

NOVEMBER 4, 2024

This article will guide you through effective strategies to learn Python for Data Science, covering essential resources, libraries, and practical applications to kickstart your journey in this thriving field. Key Takeaways Python’s simplicity makes it ideal for Data Analysis. in 2022, according to the PYPL Index.

Data Science 52

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Towards AI

APRIL 24, 2025

Unsupervised learning helps you automatically discover patterns or groupings or clustering in the data, like identifying clusters of customers with similar behaviors or preferences.

Supervised Learning 63

Supervised Learning Clustering Machine Learning Machine Learning 63

Smart Data Collective

JUNE 4, 2021

it is overwhelming to learn data science concepts and a general-purpose language like python at the same time. Exploratory Data Analysis. Exploratory data analysis is analyzing and understanding data. For exploratory data analysis use graphs and statistical parameters mean, medium, variance.

Data Science 133

Data Science Exploratory Data Analysis Machine Learning Machine Learning 133

IBM Journey to AI blog

DECEMBER 20, 2023

And retailers frequently leverage data from chatbots and virtual assistants, in concert with ML and natural language processing (NLP) technology, to automate users’ shopping experiences. Supervised machine learning Supervised machine learning is a type of machine learning where the model is trained on a labeled dataset (i.e.,

Machine Learning 92

Machine Learning Machine Learning Supervised Learning Clustering 92

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

NOVEMBER 13, 2024

Summary: Machine Learning is categorised into four main types: supervised, unsupervised, semi-supervised, and Reinforcement Learning. Each type employs distinct methodologies for Data Analysis and decision-making. UnSupervised Learning uncovers hidden patterns in unlabelled datasets.

Machine Learning 52

Machine Learning Machine Learning Supervised Learning Natural Language Processing 52

Dataconomy

MAY 25, 2023

Here are some ways AI enhances IoT devices: Advanced data analysis AI algorithms can process and analyze vast volumes of IoT-generated data. By leveraging techniques like machine learning and deep learning, IoT devices can identify trends, anomalies, and patterns within the data.

Internet of Things 160

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Dataconomy

APRIL 18, 2023

Undetectable backdoors can be implemented in any ML algorithm Machine learning Machine learning is a subfield of artificial intelligence that focuses on the development of algorithms and models that can learn from data and make predictions or decisions.

Artificial Intelligence 113

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Pickl AI

AUGUST 1, 2023

The different algorithms used for text mining are: Naive Bayes: A probabilistic algorithm used for text classification and sentiment analysis. Support Vector Machines (SVM): A supervised learning algorithm used for text classification and document clustering. So, don’t delay your growth journey and connect with Pickl.AI

Data Analysis 52

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Dataconomy

NOVEMBER 6, 2024

Traditional AI systems excel at data analysis but fall short when applied to physical tasks, which require not only vision but also sensory feedback such as touch. Sparsh is a general-purpose encoder that relies on a database of over 460,000 tactile images to teach robots to recognize and interpret touch.

AI 113

AI AI Supervised Learning Artificial Intelligence 113

ODSC - Open Data Science

OCTOBER 3, 2023

Data Analysis and Interpretation Data plays a critical role in prompt engineering. To excel in this field, you need a diverse skill set that can include a profound understanding of AI models, linguistic expertise, creative problem-solving skills, data analysis capabilities, and strong communication and collaboration skills.

Data Science 97

Data Science Data Analysis Data Analysis Supervised Learning 97

Dataconomy

MAY 6, 2025

The K-Nearest Neighbor (KNN) algorithm is an intriguing method in the realm of supervised learning, celebrated for its simplicity and intuitive approach to predicting outcomes. Often employed for both classification and regression tasks, KNN leverages the proximity of data points to derive insights and make decisions.

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K-nearest Neighbors Algorithm Machine Learning Machine Learning 91

Pickl AI

OCTOBER 9, 2023

This technology allows computers to learn from historical data, identify patterns, and make data-driven decisions without explicit programming. Unsupervised learning algorithms Unsupervised learning algorithms are a vital part of Machine Learning, used to uncover patterns and insights from unlabeled data.

Machine Learning 98

Machine Learning Machine Learning Algorithm ML 98

Towards AI

JANUARY 10, 2024

Task Orientation How were we doing machine learning almost a year ago? They are called foundation models because, with that wide set of data, you build foundations that need not change every time you adapt it to a specific business use case. And they can handle multiple types of data (images, text, video, and audio).

Machine Learning 111

Machine Learning Machine Learning Exploratory Data Analysis Supervised Learning 111

Pickl AI

JULY 17, 2023

The ability of unsupervised learning to discover similarities and differences in data makes it ideal for conducting exploratory data analysis. Unsupervised Learning Algorithms Unsupervised Learning Algorithms tend to perform more complex processing tasks in comparison to supervised learning.

Machine Learning 52

Machine Learning Machine Learning Clustering K-nearest Neighbors 52

Becoming Human

MAY 15, 2023

These communities will help you to be updated in the field, because there are some experienced data scientists posting the stuff, or you can talk with them so they will also guide you in your journey. Data Analysis After learning math now, you are able to talk with your data.

Data Science 75

Data Science Machine Learning Machine Learning Database 75

Data Science Dojo

JUNE 11, 2024

They are also known as threshold logic units (TLUs) and serve as a supervised learning algorithm that classifies data into two categories, making them a binary classifier. Moreover, they possess the risk of overfitting. Despite these limitations, shallow neural networks are a useful resource.

Natural Language Processing 195

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Pickl AI

FEBRUARY 22, 2024

Summary: Dive into programs at Duke University, MIT, and more, covering Data Analysis, Statistical quality control, and integrating Statistics with Data Science for diverse career paths. offer modules in Statistical modelling, biostatistics, and comprehensive Data Science bootcamps, ensuring practical skills and job placement.

Data Science 52

Data Science Data Analysis Data Analysis Hypothesis Testing 52

Towards AI

APRIL 4, 2024

A sector that is currently being influenced by machine learning is the geospatial sector, through well-crafted algorithms that improve data analysis through mapping techniques such as image classification, object detection, spatial clustering, and predictive modeling, revolutionizing how we understand and interact with geographic information.

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K-nearest Neighbors Machine Learning Machine Learning Decision Trees 80

Pickl AI

SEPTEMBER 17, 2024

Summary: Dimensionality reduction is a crucial technique in data analysis that simplifies complex datasets by reducing the number of features while retaining essential information. Dimensionality reduction in Machine Learning enhances model performance and improves data visualisation by focusing on the most significant dimensions.

Machine Learning 52

Machine Learning Machine Learning Data Analysis Data Analysis 52

Pickl AI

APRIL 26, 2024

Top 50+ Interview Questions for Data Analysts Technical Questions SQL Queries What is SQL, and why is it necessary for data analysis? SQL stands for Structured Query Language, essential for querying and manipulating data stored in relational databases. Explain the difference between supervised and unsupervised learning.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Pickl AI

OCTOBER 2, 2024

Genomic Analysis is crucial for various applications, including personalised medicine, cancer research, genetic disorder diagnosis, and evolutionary biology. AI Techniques Used in Genomic Analysis AI encompasses a range of techniques that can be applied to genomic Data Analysis.

Machine Learning 52

Machine Learning Machine Learning AI Artificial Intelligence 52

DataRobot Blog

DECEMBER 15, 2022

Let’s run through the process and see exactly how you can go from data to predictions. supervised learning and time series regression). Prepare your data for Time Series Forecasting. Perform exploratory data analysis. The use case will be forecasting sales for stores, which is a multi-time series problem.

Exploratory Data Analysis 81

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Dataconomy

APRIL 3, 2023

ML models are designed to learn from data and make predictions or decisions based on that data. Types of ML There are three main types of machine learning: Supervised learning: In supervised learning, the algorithm is trained on labeled data.

Artificial Intelligence 70

Artificial Intelligence Artificial Intelligence Natural Language Processing AI 70

Dataconomy

APRIL 3, 2023

ML models are designed to learn from data and make predictions or decisions based on that data. Types of ML There are three main types of machine learning: Supervised learning: In supervised learning, the algorithm is trained on labeled data.

Artificial Intelligence 70

Artificial Intelligence Artificial Intelligence Natural Language Processing AI 70

Pickl AI

NOVEMBER 18, 2024

The main types are supervised, unsupervised, and reinforcement learning, each with its techniques and applications. Supervised Learning In Supervised Learning , the algorithm learns from labelled data, where the input data is paired with the correct output. predicting house prices).

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

Pickl AI

JULY 12, 2024

Scikit-learn: A simple and efficient tool for data mining and data analysis, particularly for building and evaluating machine learning models. TensorFlow and Keras: TensorFlow is an open-source platform for machine learning.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Pickl AI

JANUARY 12, 2023

After the completion of the course, they can perform data analysis and build products using R. These include the following: Introduction to Data Science Introduction to Python SQL for Data Analysis Statistics Data Visualization with Tableau 5. Data Science Program for working professionals by Pickl.AI

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

PyImageSearch

FEBRUARY 6, 2023

But we would still apply data augmentation to ensure the model doesn’t overfit and generalize well on the test dataset. Data Analysis When working with data, especially supervised learning, it is often a best practice to check data imbalance.

Deep Learning 144

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Pickl AI

FEBRUARY 12, 2024

This theorem is crucial in inferential statistics as it allows us to make inferences about the population parameters based on sample data. Differentiate between supervised and unsupervised learning algorithms. Here is a brief description of the same.

Data Science 52

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Pickl AI

FEBRUARY 7, 2025

Features : The attributes or characteristics of the data used to make predictions. Types of Machine Learning Machine Learning is divided into three main types based on how the algorithm learns from the data: Supervised Learning In supervised learning , the algorithm is trained on labelled data.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

IBM Journey to AI blog

AUGUST 15, 2023

Foundation models are AI models trained with machine learning algorithms on a broad set of unlabeled data that can be used for different tasks with minimal fine-tuning. The model can apply information it’s learned about one situation to another using self-supervised learning and transfer learning.

Artificial Intelligence 93

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Pickl AI

SEPTEMBER 12, 2024

Data Cleaning: Raw data often contains errors, inconsistencies, and missing values. Data cleaning identifies and addresses these issues to ensure data quality and integrity. Data Visualisation: Effective communication of insights is crucial in Data Science.

Data Analyst 52

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Pickl AI

NOVEMBER 28, 2024

These techniques span different types of learning and provide powerful tools to solve complex real-world problems. Supervised Learning Supervised learning is one of the most common types of Machine Learning, where the algorithm is trained using labelled data.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

DECEMBER 4, 2024

Ensuring data quality is vital for producing reliable results. Machine Learning Understanding Machine Learning algorithms is essential for predictive analytics. This includes supervised learning techniques like linear regression and unsupervised learning methods like clustering.

Data Science 52

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