Data Science Dojo

MARCH 27, 2025

This is particularly important for relational databases, where data is stored in tables with defined relationships. Another interesting read: Master EDA Importance of Data Normalization So, we defined data normalization, and hopefully, youve got the idea. And thats why data normalization matters everywhere!

Database 195

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Becoming Human

MAY 15, 2023

Data Science is a popular as well as vast field; till date, there are a lot of opportunities in this field, and most people, whether they are working professionals or students, everyone want a transition in data science because of its scope. How much to learn? What to do next?

Data Science 75

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ODSC - Open Data Science

FEBRUARY 24, 2023

These tools will help make your initial data exploration process easy. ydata-profiling GitHub | Website The primary goal of ydata-profiling is to provide a one-line Exploratory Data Analysis (EDA) experience in a consistent and fast solution. This tool automatically detects problems in an ML dataset.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

Heartbeat

JANUARY 24, 2024

The importance of EDA in the machine learning world is well known to its users. Making visualizations is one of the finest ways for data scientists to explain data analysis to people outside the business. Exploratory data analysis can help you comprehend your data better, which can aid in future data preprocessing.

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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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Data Science EDA Decision Trees Machine Learning 52

Pickl AI

JUNE 7, 2023

How to create a Data Science Project on GitHub? Data Science being the most demanding career fields today with millions of job opportunities flooding in the market. in order to ensure that you have a great career in Data Science, one of the major requirements is to create and have a Github Data Science project.

Data Science 52

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Mlearning.ai

MAY 23, 2023

While specific requirements may vary depending on the organization and the role, here are the key skills and educational background that are required for entry-level data scientists — Skillset Mathematical and Statistical Foundation Data science heavily relies on mathematical and statistical concepts.

Data Science 52

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AWS Machine Learning Blog

SEPTEMBER 12, 2023

The machine learning (ML) model classifies new incoming customer requests as soon as they arrive and redirects them to predefined queues, which allows our dedicated client success agents to focus on the contents of the emails according to their skills and provide appropriate responses.

Data Science 129

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Data Science Dojo

AUGUST 28, 2023

Some projects may necessitate a comprehensive LLMOps approach, spanning tasks from data preparation to pipeline production. Exploratory Data Analysis (EDA) Data collection: The first step in LLMOps is to collect the data that will be used to train the LLM.

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Mlearning.ai

JULY 11, 2023

Before embarking on a data science transition, it’s crucial to be aware of these key factors. Before diving into the world of data science, it is essential to familiarize yourself with certain key aspects. In the data science industry, effective communication and collaboration play a crucial role.

Data Science 40

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Towards AI

JUNE 24, 2023

The ’31 Questions that Shape Fortune 500 ML Strategy’ highlighted key questions to assess the maturity of an ML system. A robust ML platform offers managed solutions to easily address these aspects. An MLOps workflow consists of a series of steps from data acquisition and feature engineering to training and deployment.

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Towards AI

FEBRUARY 3, 2024

From Predicting the behavior of a customer to automating many tasks, Machine learning has shown its capacity to convert raw data into actionable insights. Even though converting raw data into actionable insights, it is not determined by ML algorithms alone. The success of any ML project depends on a well-structured lifecycle.

Machine Learning 122

Machine Learning Machine Learning Exploratory Data Analysis Data Scientist 122

Towards AI

APRIL 7, 2024

Today, we’re going to discuss about the often overlooked but incredibly crucial aspect of Building ML models, i.e, Why learning to deploy the ML model is important? This involves visualizing the data and analyzing key statistics. Deploying machine learning models.

Azure 105

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ODSC - Open Data Science

APRIL 29, 2023

Check out more of the talks and workshops from industry-leading data science and AI organizations coming to ODSC East 2023 below. a comprehensive approach to the ML pipeline. Data Science Software Acceleration at the Edge Audrey Reznik Guidera｜Sr. You can see our first round of sessions here. Guillaume Moutier｜Sr.

Data Science 52

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Iguazio

DECEMBER 14, 2023

Drawing from their extensive experience in the field, the authors share their strategies, methodologies, tools and best practices for designing and building a continuous, automated and scalable ML pipeline that delivers business value. The book contains a full chapter dedicated to generative AI. Why Did the Authors Decide to Write this Book?

ML 52

ML ML Data Science Data Preparation 52

AWS Machine Learning Blog

JULY 31, 2023

Although machine learning (ML) can provide valuable insights, ML experts were needed to build customer churn prediction models until the introduction of Amazon SageMaker Canvas. Additional key topics Advanced metrics are not the only important tools available to you for evaluating and improving ML model performance.

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ODSC - Open Data Science

JULY 19, 2023

Machine Learning Operations (MLOps) can significantly accelerate how data scientists and ML engineers meet organizational needs. A well-implemented MLOps process not only expedites the transition from testing to production but also offers ownership, lineage, and historical data about ML artifacts used within the team.

Machine Learning 52

Machine Learning Machine Learning Azure Data Science 52

Pickl AI

AUGUST 28, 2024

Introduction In the rapidly evolving landscape of Machine Learning , Google Cloud’s Vertex AI stands out as a unified platform designed to streamline the entire Machine Learning (ML) workflow. This unified approach enables seamless collaboration among data scientists, data engineers, and ML engineers.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

AWS Machine Learning Blog

MAY 30, 2023

Since its introduction, we have helped hundreds of customers optimize their workloads, set guardrails, and improve the visibility of their machine learning (ML) workloads’ cost and usage. Notebooks contain everything needed to run or recreate an ML workflow. SageMaker manages creating the instance and related resources.

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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.

Decision Trees 52

Decision Trees Exploratory Data Analysis EDA Data Analysis 52

Mlearning.ai

MARCH 5, 2023

Before conducting any formal statistical analysis, it’s important to conduct exploratory data analysis (EDA) to better understand the data and identify any patterns or relationships. EDA is an approach that involves using graphical and numerical methods to summarize and visualize the data. Thank you for reading!

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Heartbeat

SEPTEMBER 28, 2023

To address this challenge, data scientists harness the power of machine learning to predict customer churn and develop strategies for customer retention. Continuous Experiment Tracking with Comet ML Comet ML is a versatile tool that helps data scientists optimize machine learning experiments.

Machine Learning 52

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Ocean Protocol

FEBRUARY 1, 2024

Challenge Overview Objective : Building upon the insights gained from Exploratory Data Analysis (EDA), participants in this data science competition will venture into hands-on, real-world artificial intelligence (AI) & machine learning (ML). You can download the dataset directly through Desights.

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Mlearning.ai

MARCH 4, 2023

Exploratory Data Analysis on Stock Market Data Photo by Lukas Blazek on Unsplash Exploratory Data Analysis (EDA) is a crucial step in data science projects. It helps in understanding the underlying patterns and relationships in the data. Data Visualization The next step is to visualize the data.

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Heartbeat

MARCH 21, 2023

We will carry out some EDA on our dataset, and then we will log the visualizations onto the Comet experimentation website or platform. Time Series Models Time series models are a type of statistical model that are used to analyze and make predictions about data that is collected over time. Without further ado, let’s begin.

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DrivenData Labs

APRIL 10, 2024

Michal Wierzbinski ¶ Place: 2nd Place Prize: $3,000 Hometown: Rabka-Zdroj (near the city of Cracow), Poland Username: xultaeculcis Social Media: GitHub , LinkedIn Background: ML Engineer specializing in building Deep Learning solutions for Geospatial industry in a cloud native fashion. What motivated you to compete in this challenge?

Deep Learning 130

Deep Learning Deep Learning Machine Learning Machine Learning 130

Ocean Protocol

SEPTEMBER 29, 2023

This data challenge took NFL player performance data and fantasy points from the last 6 seasons to calculate forecasted points to be scored in the 2024 NFL season that began Sept. AI / ML offers tools to give a competitive edge in predictive analytics, business intelligence, and performance metrics.

Cross Validation 59

Cross Validation Predictive Analytics Exploratory Data Analysis EDA 59

Heartbeat

FEBRUARY 8, 2023

This free, virtual event takes place over two days with 25+ speakers discussing the latest cutting-edge innovations in data science and machine learning. In order to accomplish this, we will perform some EDA on the Disneyland dataset, and then we will view the visualization on the Comet experimentation website or platform.

Natural Language Processing 40

Natural Language Processing Deep Learning Deep Learning Machine Learning 40

ODSC - Open Data Science

AUGUST 9, 2023

In the unceasingly dynamic arena of data science, discerning and applying the right instruments can significantly shape the outcomes of your machine learning initiatives. A cordial greeting to all data science enthusiasts! You can also get data science training on-demand wherever you are with our Ai+ Training platform.

Machine Learning 52

Machine Learning Machine Learning AWS Big Data 52

Mlearning.ai

FEBRUARY 2, 2023

How I cleared AWS Machine Learning Specialty with three weeks of preparation (I will burst some myths of the online exam) How I prepared for the test, my emotional journey during preparation, and my actual exam experience Certified AWS ML Specialty Badge source Introduction:- I recently gave and cleared AWS ML certification on 29th Dec 2022.

Machine Learning 52

Machine Learning Machine Learning AWS ML 52

Heartbeat

JANUARY 30, 2023

But they need a lot of labeled training data, and the dataset could be biased. In order to accomplish this, we will perform some EDA on the Disneyland dataset, and then we will view the visualization on the Comet experimentation website or platform. In this article, we’ll learn how to link Comet with Disneyland Sentiment Analysis.

EDA 52

EDA Machine Learning Machine Learning Exploratory Data Analysis 52

Mlearning.ai

MARCH 15, 2023

Introduction Welcome Back, Let's continue with our Data Science journey to create the Stock Price Prediction web application. The scope of this article is quite big, we will exercise the core steps of data science, let's get started… Project Layout Here are the high-level steps for this project.

Python 52

Python AWS Exploratory Data Analysis Machine Learning 52

Mlearning.ai

NOVEMBER 23, 2023

But deep down, we know we could achieve better results with a different approach, after all in ML, there’s no one-size-fits-all solution. You may need to import more libraries for EDA, preprocessing, and so on depending on the dataset you’re dealing with. Different datasets and problems may require different models for optimal results.

Supervised Learning 52

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Heartbeat

MAY 24, 2023

Create DataGrids with image data using Kangas, and load and visualize image data from hugging face Photo by Genny Dimitrakopoulou on Unsplash Visualizing data to carry out a detailed EDA, especially for image data, is critical.

Deep Learning 52

Deep Learning Deep Learning EDA ML 52

Mlearning.ai

FEBRUARY 28, 2023

Exploratory Data Analysis (EDA) Univariate EDA Price: The price of a used car is the target variable and has a highly skewed distribution, with a median value of around 53.5 Bivariate EDA Contrary to intuition, Kilometers_Driven does not seem to have a relationship with the price.

Python 52

Python EDA Exploratory Data Analysis Data Analysis 52

Mlearning.ai

MARCH 22, 2023

tolist(),columns = ["PC1","PC2","PC3"]) Array.info() Array["stroke"] = list(df["stroke"]) px.scatter_3d(Array,x = "PC1" , y= "PC2" ,z = "PC3" ,color = "stroke") Although faint, one can clearly see a linear separation in the data at the 0 of the x-axis.

Data Scientist 52

Data Scientist Machine Learning Machine Learning EDA 52

Heartbeat

JANUARY 25, 2023

Build and deploy your own sentiment classification app using Python and Streamlit Source:Author Nowadays, working on tabular data is not the only thing in Machine Learning (ML). Data formats like image, video, text, etc., This approach is mostly referred to for small datasets where ML models can not be effective.

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