Smart Data Collective

OCTOBER 17, 2022

Big data is shaping our world in countless ways. Data powers everything we do. Exactly why, the systems have to ensure adequate, accurate and most importantly, consistent data flow between different systems. It stores the data of every partner business entity in an exclusive micro-DB while storing millions of databases.

Data Pipeline 145

Data Pipeline Data Warehouse ETL Data Lakes 145

Dataconomy

MAY 16, 2023

Machine learning engineer vs data scientist: The growing importance of both roles Machine learning and data science have become integral components of modern businesses across various industries. Machine learning, a subset of artificial intelligence , enables systems to learn and improve from data without being explicitly programmed.

Data Scientist 156

Data Scientist ML ML Machine Learning 156

Pickl AI

NOVEMBER 4, 2024

Its flexibility allows you to produce high-quality graphs and charts, making it perfect for exploratory Data Analysis. Use cases for Matplotlib include creating line plots, histograms, scatter plots, and bar charts to represent data insights visually.

Data Science 52

Data Science Python Machine Learning Machine Learning 52

ODSC - Open Data Science

AUGUST 9, 2023

The inferSchema parameter is set to True to infer the data types of the columns, and header is set to True to use the first row as headers.

Machine Learning 52

Machine Learning Machine Learning AWS Big Data 52

Towards AI

APRIL 19, 2024

LLMs are broadly incapable of solving such multifaceted tasks, contrary to most text analysis tools, which can seamlessly solve all of the mentioned tasks. It’s an open-source Python package for Exploratory Data Analysis of text.

Analytics 104

Analytics Analytics Data Analysis Data Analysis 104

Women in Big Data

APRIL 17, 2024

Exploratory Data Analysis (EDA): We unpacked the importance of EDA, the process of uncovering patterns and relationships within your data. Data Exploration: Unveiling the Story Within The workshop equipped you with skills to analyze sample A/B experiment data and perform exploratory data analysis (EDA).

Exploratory Data Analysis 52

Exploratory Data Analysis EDA Machine Learning Machine Learning 52

Mlearning.ai

MAY 5, 2023

You should be comfortable working with data structures, algorithms, and libraries like NumPy, Pandas, and TensorFlow. Data Analysis Skills : To work with LLMs effectively, you should be comfortable with data analysis techniques.

Natural Language Processing 98

Natural Language Processing Deep Learning Deep Learning Exploratory Data Analysis 98

Pickl AI

DECEMBER 3, 2024

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. Loading the dataset allows you to begin exploring and manipulating the data. During EDA, you can: Check for missing values.

Python 52

Python ML ML Exploratory Data Analysis 52

Mlearning.ai

MAY 23, 2023

Blind 75 LeetCode Questions - LeetCode Discuss Data Manipulation and Analysis Proficiency in working with data is crucial. This includes skills in data cleaning, preprocessing, transformation, and exploratory data analysis (EDA).

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Data Science Blog

FEBRUARY 23, 2023

Along with the rapid progress of deep learning mentioned above, a lot of hypes and catchphrases regarding big data and machine learning were made, and an interesting one is “Data is the new oil.” ” That might have been said only because big data is sources of various industries.

Supervised Learning 264

Supervised Learning Machine Learning Machine Learning Deep Learning 264

Pickl AI

JULY 18, 2023

Dealing with large datasets: With the exponential growth of data in various industries, the ability to handle and extract insights from large datasets has become crucial. Data science equips you with the tools and techniques to manage big data, perform exploratory data analysis, and extract meaningful information from complex datasets.

Computer Science 52

Computer Science Computer Science Data Science Machine Learning 52

Pickl AI

JULY 20, 2023

Defining clear objectives and selecting appropriate techniques to extract valuable insights from the data is essential. Here are some project ideas suitable for students interested in big data analytics with Python: 1. Sentiment Analysis on Social Media Data: Gather tweets or reviews from a social media platform using APIs.

Analytics 40

Analytics Analytics Big Data Big Data 40

Flipboard

MARCH 22, 2023

You’re redirected to the Prepare page, where you can add transformations and analyses to the data. Data Wrangler makes it easy to ingest data and perform data preparation tasks such as exploratory data analysis, feature selection, and feature engineering. Bosco Albuquerque is a Sr.

AWS 123

AWS Data Preparation Azure Data Scientist 123

Pickl AI

JULY 25, 2023

They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. With expertise in programming languages like Python , Java , SQL, and knowledge of big data technologies like Hadoop and Spark, data engineers optimize pipelines for data scientists and analysts to access valuable insights efficiently.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

DrivenData Labs

APRIL 10, 2024

Combining deep and practical understanding of technology, computer vision and AI with experience in big data architectures. A data geek by heart. What motivated you to compete in this challenge?

Deep Learning 130

Deep Learning Deep Learning Machine Learning Machine Learning 130

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.

Data Science 40

Data Science Exploratory Data Analysis Azure Power BI 40

Pickl AI

FEBRUARY 22, 2024

MicroMasters Program in Statistics and Data Science MIT – edX 1 year 2 months (INR 1,11,739) This program integrates Data Science, Statistics, and Machine Learning basics. It emphasises probabilistic modeling and Statistical inference for analysing big data and extracting information.

Data Science 52

Data Science Hypothesis Testing Data Analysis Data Analysis 52

Pickl AI

MARCH 3, 2023

There are other types of Statistical Analysis as well which includes the following: Predictive Analysis: Significantly, it is the type of Analysis useful for forecasting future events based on present and past data. Moreover, it helps make informed decisions and encourages efficient decision-making processes.

Exploratory Data Analysis 40

Exploratory Data Analysis Hypothesis Testing Data Analyst Data Scientist 40

Pickl AI

JULY 10, 2023

As a programming language it provides objects, operators and functions allowing you to explore, model and visualise data. The programming language can handle Big Data and perform effective data analysis and statistical modelling.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

SEPTEMBER 5, 2024

Unified Data Services: Azure Synapse Analytics combines big data and data warehousing, offering a unified analytics experience. Azure’s global network of data centres ensures high availability and performance, making it a powerful platform for Data Scientists to leverage for diverse data-driven projects.

Azure 52

Azure Data Scientist Data Science Machine Learning 52

Pickl AI

NOVEMBER 15, 2023

Data scientists can explore, experiment, and derive valuable insights without the constraints of a predefined structure. This capability empowers organizations to uncover hidden patterns, trends, and correlations in their data, leading to more informed decision-making.

Data Lakes 52

Data Lakes Data Warehouse Database ETL 52

Pickl AI

APRIL 26, 2024

I conducted thorough data validation, collaborated with stakeholders to identify the root cause, and implemented corrective measures to ensure data integrity. I would perform exploratory data analysis to understand the distribution of customer transactions and identify potential segments.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

AWS Machine Learning Blog

AUGUST 12, 2024

Figure 7: Using SageMaker Data Wrangler’s chat for data prep to run SQL statements Check for data quality SageMaker Canvas also provides exploratory data analysis (EDA) capabilities that allow you to gain deeper insights into the data prior to the ML model build step.

ML 121

ML ML AWS AI 121

Pickl AI

FEBRUARY 12, 2024

Course Topics: Introduction to Data Science Data Acquisition and Cleaning Exploratory Data Analysis (EDA) Statistical Analysis Programming for Data Science Machine Learning Basics Supervised Learning Algorithms Unsupervised Learning Algorithms Introduction to Deep Learning Big Data and Cloud Computing Top Data Science Interview Questions and Expert (..)

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Pickl AI

JUNE 12, 2023

A Data Scientist requires to be able to visualize quickly the data before creating the model and Tableau is helpful for that. Here are several ways you can leverage Tableau for data science tasks: Data exploration and visualization: Tableau provides you with an intuitive and interactive interface for exploring and visualizing data.

Tableau 52

Tableau Data Science Data Scientist Data Analysis 52

ODSC - Open Data Science

JULY 19, 2023

Model Development (Inner Loop): The inner loop element consists of your iterative data science workflow. A typical workflow is illustrated here from data ingestion, EDA (Exploratory Data Analysis), experimentation, model development and evaluation, to the registration of a candidate model for production.

Machine Learning 52

Machine Learning Machine Learning Azure Data Science 52

Pickl AI

APRIL 10, 2023

So, if you are eyeing your career in the data domain, this blog will take you through some of the best colleges for Data Science in India. There is a growing demand for employees with digital skills The world is drifting towards data-based decision making In India, a technology analyst can make between ₹ 5.5 Lakhs to ₹ 11.0

Data Science 52

Data Science Machine Learning Machine Learning Python 52

Pickl AI

JANUARY 12, 2023

Additionally, it involves learning the mathematical and computational tools that form the core of Data Science. Besides, you will also learn how to use the tools that will eventually help in making data-driven decisions. This particular skill will help you upskill yourself and gain professional excellence.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

SEPTEMBER 12, 2024

B Big Data : Large datasets characterised by high volume, velocity, variety, and veracity, requiring specialised techniques and technologies for analysis. Deep Learning : A subset of Machine Learning that uses Artificial Neural Networks with multiple hidden layers to learn from complex, high-dimensional data.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Snorkel AI

MAY 12, 2023

Compute, big data, large commoditized models—all important stages. But now we’re entering a period where data investments have massive returns from all performance as well as business impact.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Snorkel AI

MAY 12, 2023

Compute, big data, large commoditized models—all important stages. But now we’re entering a period where data investments have massive returns from all performance as well as business impact.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Towards AI

MAY 8, 2025

Unless you have very specific performance needs, Pandas will efficiently handle tasks like quick exploratory analysis and visualizations. You are doing a quick exploratory data analysis. Your workflows involve lots of data visualization. Use Pandas when: Your dataset fits comfortably in memory.

Data Engineering 82

Data Engineering Data Engineering Data Engineering Data Engineer 82