Pickl AI

MARCH 7, 2024

Applications: It is extensively used for statistical analysis, data visualisation, and machine learning tasks such as regression, classification, and clustering. Scikit-learn Functionality: Scikit-learn is a simple and efficient tool for data mining and analysis, built on NumPy, SciPy, and matplotlib.

Data Science 52

Data Science Machine Learning Machine Learning Python 52

Pickl AI

JUNE 7, 2023

Analysing Netflix Movies and TV Shows One of the most enticing real-world Data Science projects Github can include the project focusing to analyse Netflix movies and TV shows. Using Netflix user data, you need to undertake Data Analysis for running workflows like EDA, Data Visualisation and interpretation.

Data Science 52

Data Science Deep Learning Deep Learning Clustering 52

Smart Data Collective

JUNE 4, 2021

Here are the chronological steps for the data science journey. First of all, it is important to understand what data science is and is not. Data science should not be used synonymously with data mining. Mathematics, statistics, and programming are pillars of data science. Exploratory Data Analysis.

Data Science 105

Data Science Exploratory Data Analysis Machine Learning Machine Learning 105

ODSC - Open Data Science

FEBRUARY 8, 2023

Then, an analyst prepares them for reporting (via data visualization tools like Google Data Studio). The BigQuery tool was designed to be the centerpiece of data analysis. By using it, managers reduce the costs of creating the cloud system and gain more time to analyze data.

Database 97

Database Business Intelligence Business Intelligence Big Data 97

Pickl AI

MAY 10, 2023

Certainly, these predictions and classification help in uncovering valuable insights in data mining projects. ML algorithms fall into various categories which can be generally characterised as Regression, Clustering, and Classification. Both the hierarchical clustering and contentious clustering methods are seen as dendrogram.

Clustering 52

Clustering Decision Trees Machine Learning Machine Learning 52

Dataconomy

JULY 28, 2023

How to become a data scientist Data transformation also plays a crucial role in dealing with varying scales of features, enabling algorithms to treat each feature equally during analysis Noise reduction As part of data preprocessing, reducing noise is vital for enhancing data quality.

Power BI 91

Power BI Data Preparation Exploratory Data Analysis Machine Learning 91

Towards AI

MARCH 17, 2023

Random variable: Statistics and data mining are concerned with data. How do we link sample spaces and events to data? That choice will be random [Even though there are methods to choose k sample but still this is random]. and those chosen people will be sampled from all student's sample space.

Hypothesis Testing 97

Hypothesis Testing Data Mining Data Mining Data Mining 97

Pickl AI

JULY 17, 2023

Therefore, it mainly deals with unlabelled data. The ability of unsupervised learning to discover similarities and differences in data makes it ideal for conducting exploratory data analysis. There are different kinds of unsupervised learning algorithms, including clustering, anomaly detection, neural networks, etc.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Clustering 52

Pickl AI

JULY 18, 2023

While it may not be a traditional programming language, SQL plays a crucial role in Data Science by enabling efficient querying and extraction of data from databases. SQL’s powerful functionalities help in extracting and transforming data from various sources, thus helping in accurate data analysis.

Data Science 52

Data Science SQL Data Scientist Apache Hadoop 52

Mlearning.ai

JUNE 27, 2023

A Complete Guide about K-Means, K-Means ++, K-Medoids & PAM’s in K-Means Clustering. A Complete Guide about K-Means, K-Means ++, K-Medoids & PAM’s in K-Means Clustering. To address such tasks and uncover behavioral patterns, we turn to a powerful technique in Machine Learning called Clustering. K = 3 ; 3 Clusters.

Clustering 52

Clustering Algorithm Data Analyst Machine Learning 52

PyImageSearch

JUNE 19, 2023

By the end of the lesson, readers will have a solid grasp of the underlying principles that enable these applications to make suggestions based on data analysis. Recommendation Techniques Data mining techniques are incredibly valuable for uncovering patterns and correlations within data.

K-nearest Neighbors 56

K-nearest Neighbors Clustering Algorithm Deep Learning 56

Dataconomy

APRIL 27, 2023

Conversely, OLAP systems are optimized for conducting complex data analysis and are designed for use by data scientists, business analysts, and knowledge workers. OLAP systems support business intelligence, data mining, and other decision support applications.

Database 159

Database Data Scientist Data Mining Data Mining 159

Data Science Blog

FEBRUARY 23, 2023

And importantly, starting naively annotating data might become a quick solution rather than thinking about how to make uses of limited labels if extracting data itself is easy and does not cost so much. In this case, original data distribution have two clusters of circles and triangles and a clear border can be drawn between them.

Supervised Learning 264

Supervised Learning Machine Learning Machine Learning Deep Learning 264

Smart Data Collective

SEPTEMBER 17, 2020

One new feature is the ability to create a radius, which wouldn’t be possible without the highly refined data mining and analytics features embedded in the core of the Google Maps algorithm. The Emerging Role of Big Data with Google Analytics. This is where web-based map developers such as maptive.com have tools that can help.

Big Data 132

Big Data Big Data Data Mining Data Mining 132

DagsHub

APRIL 21, 2024

Scikit-learn Scikit-learn is a machine learning library in Python that is majorly used for data mining and data analysis. Kubernetes manages the deployment and scaling of containerized applications across a cluster of compute nodes , ensuring high availability and resource efficiency.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

Pickl AI

MAY 16, 2023

Expansive Hiring The IT and service sector is actively hiring Data Scientists. In fact, these industries majorly employ Data Scientists. Python, Data Mining, Analytics and ML are one of the most preferred skills for a Data Scientist. Wrapping it up !!!

Data Scientist 52

Data Scientist Data Science SQL Python 52

Mlearning.ai

MAY 23, 2023

Once the data is acquired, it is maintained by performing data cleaning, data warehousing, data staging, and data architecture. Data processing does the task of exploring the data, mining it, and analyzing it which can be finally used to generate the summary of the insights extracted from the data.

Data Science 52

Data Science Decision Trees Deep Learning Deep Learning 52