Data Science Dojo

MAY 24, 2023

By following best practices in algorithm selection, data preprocessing, model evaluation, and deployment, we unlock the true potential of machine learning and pave the way for innovation and success. In this blog, we focus on machine learning practices—the essential steps that unlock the potential of this transformative technology.

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Towards AI

MARCH 28, 2023

Explained from scratch, step by step Some time ago, I found myself having to explain the tree-based algorithms to a person who was into mathematics… but with zero knowledge of data science. Join thousands of data leaders on the AI newsletter. From research to projects and ideas.

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Data Science Dojo

MAY 27, 2024

In this blog, we will explore the details of both approaches and navigate through their differences. These methodologies represent distinct paradigms in AI, each with unique capabilities and applications. Yet the crucial question arises: Which of these emerges as the foremost driving force in AI innovation? What is Generative AI?

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Data Science Dojo

FEBRUARY 14, 2024

Feature Engineering encompasses a diverse array of techniques, including Feature Transformation, Feature Construction, Feature Selection, Feature Scaling, and Feature Extraction, each playing a crucial role in refining and optimizing the representation of data for machine learning tasks.

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Pickl AI

FEBRUARY 2, 2025

One of its key techniques is associative classification in data mining , which combines association rule mining with classification to improve predictive modelling. This blog aims to explain associative classification in data mining, its applications, and its role in various industries.

Data Mining 52

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Towards AI

AUGUST 5, 2023

Photo by Ed Robertson on Unsplash The Gini index is a popular tool within Data Science that is responsible for deciding how decision trees split. A Gini index of 0 indicates perfect inequality where… Read the full blog for free on Medium. Join thousands of data leaders on the AI newsletter.

Machine Learning 98

Machine Learning Machine Learning Decision Trees Data Science 98

IBM Journey to AI blog

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

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Dataconomy

JULY 24, 2023

If you’ve found yourself asking, “How to become a data scientist?” In this detailed guide, we’re going to navigate the exciting realm of data science, a field that blends statistics, technology, and strategic thinking into a powerhouse of innovation and insights. ” you’re in the right place.

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Data Science Dojo

DECEMBER 28, 2023

Imagine a world where your business could make smarter decisions, predict customer behavior with astonishing accuracy, and automate tasks that used to take hours of manual labor. That world is not science fiction—it’s the reality of machine learning (ML). Master the machine learning algorithms in this blog 4.

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Mlearning.ai

FEBRUARY 6, 2024

Exploratory Data Analysis(EDA)on Biological Data: A Hands-On Guide Unraveling the Structural Data of Proteins, Part II — Exploratory Data Analysis Photo from Pexels In a previous post, I covered the background of this protein structure resolution data set, including an explanation of key data terminology and details on how to acquire the data.

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DrivenData Labs

MAY 24, 2023

Currently pursuing graduate studies at NYU's center for data science. Alejandro Sáez: Data Scientist with consulting experience in the banking and energy industries currently pursuing graduate studies at NYU's center for data science. What motivated you to compete in this challenge? The federated learning aspect.

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Towards AI

SEPTEMBER 30, 2024

Unlike other algorithms, which rely on a single model to make predictions, Gradient Boosting uses a series of weak models (often decision trees), each learning from the mistakes of the one before it. Join thousands of data leaders on the AI newsletter.

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Towards AI

OCTOBER 3, 2024

Instead of relying on one model, ensemble methods build multiple models that may use: Different algorithms: For example, one model might use Decision Trees while another uses Logistic Regression.The same algorithm but trained on different subsets of data: Even… Read the full blog for free on Medium.

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Mlearning.ai

MARCH 26, 2023

Embark on Your Data Science Journey through In-Depth Projects and Hands-on Learning Photo by Wes Hicks on Unsplash Data science, as an emerging field, is constantly evolving and bringing forth innovative solutions to complex problems. I’ve handpicked a few Kaggle projects covering a range of data science concepts.

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Pickl AI

MAY 31, 2023

With the expanding field of Data Science, the need for efficient and skilled professionals is increasing. Its efficacy may allow kids from a young age to learn Python and explore the field of Data Science. Its efficacy may allow kids from a young age to learn Python and explore the field of Data Science.

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Pickl AI

SEPTEMBER 23, 2024

Summary: The blog explores the synergy between Artificial Intelligence (AI) and Data Science, highlighting their complementary roles in Data Analysis and intelligent decision-making. This article explores how AI and Data Science complement each other, highlighting their combined impact and potential.

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ODSC - Open Data Science

MAY 31, 2023

The combination of data streaming and machine learning (ML) enables you to build one scalable, reliable, but also simple infrastructure for all machine learning tasks using the Apache Kafka ecosystem. A very common pattern for building machine learning infrastructure is to ingest data via Kafka into a data lake.

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Mlearning.ai

MAY 23, 2023

Hey guys, in this blog we will see some of the most asked Data Science Interview Questions by interviewers in [year]. Data science has become an integral part of many industries, and as a result, the demand for skilled data scientists is soaring. What is Data Science?

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Data Science Dojo

SEPTEMBER 13, 2024

The ones discussed in this blog are the AUC (Area Under the Curve) and ROC (Receiver Operating Characteristic). Read more about classification using decision trees Threshold Selection In practice, ROC curves greatly help in the selection of the optimal threshold for classification problems.

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Towards AI

DECEMBER 18, 2024

You're not ready for neural networks if you cant explain Linear Regression or Decision Trees. … Read the full blog for free on Medium. Join thousands of data leaders on the AI newsletter. These simple models work wonders for small datasets and lay a solid foundation for understanding the basics.

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Data Science Dojo

JULY 23, 2024

It has led to advanced techniques for data management, where each tactic is based on the type of data and the way to handle it. Categorical data is one such form of information that is handled by ML models using different methods. In this blog, we will explore the basics of categorical data.

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Pickl AI

JULY 18, 2023

Data Science helps businesses uncover valuable insights and make informed decisions. Programming for Data Science enables Data Scientists to analyze vast amounts of data and extract meaningful information. 8 Most Used Programming Languages for Data Science 1.

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Pickl AI

JULY 10, 2023

What is R in Data Science? As a programming language it provides objects, operators and functions allowing you to explore, model and visualise data. How is R Used in Data Science? R is a popular programming language and environment widely used in the field of data science.

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Pickl AI

MAY 24, 2023

To help you understand Python Libraries better, the blog will explain a Python Libraries for Data Science List which you can learn about. This may include for instance in Machine Learning, Data Science, Data Visualisation, image and Data Manipulation. What is a Python Library?

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Towards AI

MARCH 28, 2024

Back when I started learning ML, some of my professors would simply throw a formula on the screen and tell us “This is the loss function for a decision tree” and that was it. I was always asking myself how those smart scientists could understand math… Read the full blog for free on Medium.

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Data Science Dojo

APRIL 10, 2023

In data mining, popular algorithms include decision trees, support vector machines, and k-means clustering. While summing up… In conclusion, data mining is a powerful tool that can help businesses and organizations extract valuable insights from their data.

Data Mining 195

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phData

MARCH 6, 2023

If you spend even a few minutes on KNIME’s website or browsing through their whitepapers and blog posts, you’ll notice a common theme: a strong emphasis on data science and predictive modeling. Building a Decision Tree Model in KNIME The next predictive model that we want to talk about is the decision tree.

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IBM Journey to AI blog

DECEMBER 20, 2023

ML is a computer science, data science and artificial intelligence (AI) subset that enables systems to learn and improve from data without additional programming interventions. Naïve Bayes algorithms include decision trees , which can actually accommodate both regression and classification algorithms.

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ODSC - Open Data Science

MARCH 29, 2024

They have years of experience in investigations and have succeeded in their careers without the use of data science or AI. You know that walking into them and starting to talk about random forests, gradient boosting, area under the ROC curve, and other such data science concepts is a nonstarter.

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Mlearning.ai

APRIL 6, 2023

⚠ You can solve the below-mentioned questions from this blog ⚠ ✔ What if I am building Low code — No code ML automation tool and I do not have any orchestrator or memory management system ? will my data help in this ? ▶ Type of Data : The type of data you have can also affect the choice of the classification algorithm.

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

Pickl AI

JANUARY 2, 2025

Summary: Entropy in Machine Learning quantifies uncertainty, driving better decision-making in algorithms. It optimises decision trees, probabilistic models, clustering, and reinforcement learning. Entropy aids in splitting data, refining predictions, and balancing exploration-exploitation.

Machine Learning 52

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Towards AI

OCTOBER 4, 2023

Weak learners or base models: These are the different algorithms used in a collection of machine learning base models in the ensemble, these models can be logistic regression, SVM, decision trees, linear regression, random forest, etc. Join thousands of data leaders on the AI newsletter.

Decision Trees 52

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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.

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Pickl AI

DECEMBER 14, 2023

The blog delves into their applications, emphasizing real-world examples in healthcare, finance, retail, and technology. From predicting patient outcomes to optimizing inventory management, these techniques empower decision-makers to navigate data landscapes confidently, fostering informed and strategic decision-making.

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Pickl AI

APRIL 28, 2023

With more than 650% growth since 2012, Data Science has emerged as one of the most sought-after technologies. With the new developments in this domain, Data Science presents a picture of futuristic technology. A Data Scientist’s average salary in India is up to₹ 8.0 Data Scientist Salary in Hyderabad : ₹ 8.0

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Heartbeat

OCTOBER 31, 2023

Before continuing, revisit the lesson on decision trees if you need help understanding what they are. We can compare the performance of the Bagging Classifier and a single Decision Tree Classifier now that we know the baseline accuracy for the test dataset. Bagging is a development of this idea.

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Data Science Dojo

AUGUST 16, 2023

Learn more about NLP in this blog —-> Applications of Natural Language Processing The transformer has been so successful because it is able to learn long-range dependencies between words in a sentence. To tackle this challenge, researchers are developing new techniques to pre-train transformer models on large datasets.

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