Pickl AI

DECEMBER 3, 2024

Introduction Data preprocessing is a critical step in the Machine Learning pipeline, transforming raw data into a clean and usable format. With the explosion of data in recent years, it has become essential for data scientists and Machine Learning practitioners to understand and effectively apply preprocessing techniques.

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Data Science Dojo

AUGUST 28, 2023

Similar to traditional Machine Learning Ops (MLOps), LLMOps necessitates a collaborative effort involving data scientists, DevOps engineers, and IT professionals. Some projects may necessitate a comprehensive LLMOps approach, spanning tasks from data preparation to pipeline production.

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Towards AI

JUNE 5, 2023

As such, my intention with this blog is not to duplicate those definitions but rather to encourage you to question and evaluate your current ML strategy. While ML algorithms & code play a crucial role in success, it’s just a small piece of the large puzzle. Source: Image by the author.

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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.

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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. Collaboration] How can multiple data scientists collaborate in real-time on the same dataset?

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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. A test endpoint is deployed for testing purposes.

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The MLOps Blog

MAY 31, 2023

And eCommerce companies have a ton of use cases where ML can help. The problem is, with more ML models and systems in production, you need to set up more infrastructure to reliably manage everything. And because of that, many companies decide to centralize this effort in an internal ML platform. But how to build it?

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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. It also enables you to evaluate the models using advanced metrics as if you were a data scientist.

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Pickl AI

NOVEMBER 4, 2024

Its robust ecosystem of libraries and frameworks tailored for Data Science, such as NumPy, Pandas, and Scikit-learn, contributes significantly to its popularity. Moreover, Python’s straightforward syntax allows Data Scientists to focus on problem-solving rather than grappling with complex code.

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AWS Machine Learning Blog

APRIL 6, 2023

& AWS Machine Learning Solutions Lab (MLSL) Machine learning (ML) is being used across a wide range of industries to extract actionable insights from data to streamline processes and improve revenue generation. For further assistance in terms of designing and developing ML solutions, please free to get in touch with the MLSL team.

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Mlearning.ai

MAY 23, 2023

Answering one of the most common questions I get asked as a Senior Data Scientist — What skills and educational background are necessary to become a data scientist? Photo by Eunice Lituañas on Unsplash To become a data scientist, a combination of technical skills and educational background is typically required.

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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.

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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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Heartbeat

FEBRUARY 13, 2023

It is designed to make it easy to track and monitor experiments and conduct exploratory data analysis (EDA) using popular Python visualization frameworks. Introducing Kangas A powerful software application for working with large amounts of multimedia data. We pay our contributors, and we don’t sell ads.

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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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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.

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Ocean Protocol

MAY 24, 2024

The challenge required a detailed analysis of Google Trends data, integration of additional data sources, and the application of advanced ML methods to predict market behaviors. Data scientists across various expertise levels engaged in this challenge to determine Google Trends’ impact on cryptocurrency valuations.

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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.

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Becoming Human

MAY 15, 2023

Note : Now, Start joining Data Science communities on social media platforms. 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.

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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.

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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 is poised to address these exact challenges.

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Mlearning.ai

MARCH 22, 2023

Principal Component Analysis(PCA) is an essential algorithm in a data scientist's toolkit. This makes it particularly useful for analyzing large datasets with many variables, where it can be difficult to visualize and interpret the data. . BECOME a WRITER at MLearning.ai

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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.

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ODSC - Open Data Science

APRIL 29, 2023

a comprehensive approach to the ML pipeline. Latest trends/methods in Feature Engineering for Time Series Forecasting Dr. Joshua Gordon｜Senior Data Scientist｜DotData This workshop will introduce you to the fundamentals and practical applications of feature engineering as they apply to time series forecasting.

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Ocean Protocol

MARCH 11, 2024

METAR, Miami International Airport (KMIA) on March 9, 2024, at 15:00 UTC In the recently concluded data challenge hosted on Desights.ai , participants used exploratory data analysis (EDA) and advanced artificial intelligence (AI) techniques to enhance aviation weather forecasting accuracy.

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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.

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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?

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Pickl AI

JANUARY 3, 2024

The growing application of Machine Learning also draws interest towards its subsets that add power to ML models. Key takeaways Feature engineering transforms raw data for ML, enhancing model performance and significance. EDA, imputation, encoding, scaling, extraction, outlier handling, and cross-validation ensure robust models.

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Pickl AI

JUNE 7, 2023

Data Science projects require you perform different projects and track changes in your project using a version code. If you want to become an efficient Data Scientist and grab that job role you’ve been looking for, you need to work on Github for Data Science projects.

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Pickl AI

JULY 12, 2024

Here are a few of the key concepts that you should know: Machine Learning (ML) This is a type of AI that allows computers to learn without being explicitly programmed. Machine Learning algorithms are trained on large amounts of data, and they can then use that data to make predictions or decisions about new data.

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Mlearning.ai

FEBRUARY 28, 2023

As a data scientist at Cars4U, I had to come up with a pricing model that can effectively predict the price of used cars and can help the business in devising profitable strategies using differential pricing. Bivariate EDA Contrary to intuition, Kilometers_Driven does not seem to have a relationship with the price.

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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. We pay our contributors, and we don’t sell ads.

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Mlearning.ai

JULY 11, 2023

For instance, feature engineering and exploratory data analysis (EDA) often require the use of visualization libraries like Matplotlib and Seaborn. In the data science industry, effective communication and collaboration play a crucial role. Moreover, tools like Power BI and Tableau can produce remarkable results.

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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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ODSC - Open Data Science

AUGUST 9, 2023

This is a straightforward and mostly clear-cut question — most of us can likely classify a dish as a dessert or not simply by reading its name, which makes it an excellent candidate for a simple ML model. Step 3: Train, Test, and Evaluate Model Once the data is processed and transformed, we can split it into a training set and a testing set.

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Heartbeat

FEBRUARY 6, 2024

From the above EDA, it is clear that the room's temperature, light, and CO2 levels are good occupancy indicators. Editorially independent, Heartbeat is sponsored and published by Comet, an MLOps platform that enables data scientists & ML teams to track, compare, explain, & optimize their experiments.

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Snorkel AI

AUGUST 9, 2023

ML practitioners are increasingly coming to appreciate that while foundation models like LLMs provide a fantastic foundation for AI applications, best results are achieved with additional data-centric development. We corrected these via prompt where possible and then later via additional labeled data for fine-tuning.

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