Towards AI

JULY 17, 2023

Later on, we will train a classifier for Car Evaluation data, by Encoding the data, Feature extraction and Developing classifier model using various algorithms and evaluate the results. Pyspark MLlib is a wrapper over PySpark Core to do data analysis using machine-learning algorithms.

ML 91

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Mlearning.ai

FEBRUARY 15, 2024

Data Science Project — Predictive Modeling on Biological Data Part III — A step-by-step guide on how to design a ML modeling pipeline with scikit-learn Functions. Photo by Unsplash Earlier we saw how to collect the data and how to perform exploratory data analysis. You can refer part-I and part-II of this article.

Data Science 52

Data Science Decision Trees Exploratory Data Analysis Cross Validation 52

Data Science Dojo

JUNE 1, 2023

The course covers topics such as linear regression, logistic regression, and decision trees. Take the first step by enrolling in our comprehensive data science course. Gain expertise in data analysis, deep learning, neural networks, and more. Step up your game and make accurate predictions based on vast datasets.

Machine Learning 195

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Dataconomy

JULY 18, 2023

By leveraging artificial intelligence algorithms and data analytics, manufacturers can streamline their quoting process, improve accuracy, and gain a competitive edge in the market. AI-powered quoting systems leverage advanced algorithms to analyze vast amounts of data accurately.

AI 91

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Pickl AI

JANUARY 29, 2024

Summary: In the tech landscape of 2024, the distinctions between Data Science and Machine Learning are pivotal. Data Science extracts insights, while Machine Learning focuses on self-learning algorithms. The collective strength of both forms the groundwork for AI and Data Science, propelling innovation. billion by 2029.

Data Science 52

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Pickl AI

APRIL 3, 2023

Accordingly, Machine Learning allows computers to learn and act like humans by providing data. Apparently, ML algorithms ensure to train of the data enabling the new data input to make compelling predictions and deliver accurate results. What is Supervised Learning? What is Unsupervised Learning?

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Dataconomy

MAY 25, 2023

These devices collect and exchange data, creating a massive ecosystem that connects the physical and digital worlds. By leveraging advanced algorithms and machine learning techniques, IoT devices can analyze and interpret data in real-time, enabling them to make informed decisions and take autonomous actions.

Internet of Things 160

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Pickl AI

APRIL 26, 2024

Top 50+ Interview Questions for Data Analysts Technical Questions SQL Queries What is SQL, and why is it necessary for data analysis? SQL stands for Structured Query Language, essential for querying and manipulating data stored in relational databases. What are the advantages and disadvantages of decision trees ?

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Dataconomy

AUGUST 9, 2023

By scrutinizing data packets that constitute network traffic, NTA aims to establish baselines of normal behavior, detect deviations, and take appropriate actions. But as in every aspect of our lives, Machine Learning algorithms and artificial intelligence help us in network traffic analysis.

Machine Learning 91

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Pickl AI

JANUARY 3, 2024

Feature engineering in machine learning is a pivotal process that transforms raw data into a format comprehensible to algorithms. Through Exploratory Data Analysis , imputation, and outlier handling, robust models are crafted. Time features Objective: Extracting valuable information from time-related data.

Machine Learning 52

Machine Learning Machine Learning Exploratory Data Analysis Cross Validation 52

Defined.ai blog

AUGUST 10, 2023

Businesses must understand how to implement AI in their analysis to reap the full benefits of this technology. In the following sections, we will explore how AI shapes the world of financial data analysis and address potential challenges and solutions.

Business Intelligence 52

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IBM Journey to AI blog

DECEMBER 19, 2023

Common machine learning algorithms for supervised learning include: K-nearest neighbor (KNN) algorithm : This algorithm is a density-based classifier or regression modeling tool used for anomaly detection. Regression modeling is a statistical tool used to find the relationship between labeled data and variable data.

Machine Learning 72

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ODSC - Open Data Science

AUGUST 15, 2023

Big Data Analysis with PySpark Bharti Motwani | Associate Professor | University of Maryland, USA Ideal for business analysts, this session will provide practical examples of how to use PySpark to solve business problems. Finally, you’ll discuss a stack that offers an improved UX that frees up time for tasks that matter.

Machine Learning 52

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phData

MAY 19, 2023

But in its raw form, this data is just noise until it is analyzed and transformed into meaningful information. This is where data science steps in. As an interdisciplinary field, data science leverages scientific methods, algorithms, and systems to extract insights from structured and unstructured data.

Decision Trees 52

Decision Trees Data Science Machine Learning Machine Learning 52

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.

Exploratory Data Analysis 52

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Pickl AI

FEBRUARY 12, 2024

Technical Proficiency Data Science interviews typically evaluate candidates on a myriad of technical skills spanning programming languages, statistical analysis, Machine Learning algorithms, and data manipulation techniques. Differentiate between supervised and unsupervised learning algorithms.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Pickl AI

OCTOBER 18, 2023

Data serves as the backbone of informed decision-making, and the accuracy, consistency, and reliability of data directly impact an organization’s operations, strategy, and overall performance. Informed Decision-making High-quality data empowers organizations to make informed decisions with confidence.

Data Quality 52

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Pickl AI

NOVEMBER 2, 2023

A cheat sheet for Data Scientists is a concise reference guide, summarizing key concepts, formulas, and best practices in Data Analysis, statistics, and Machine Learning. It serves as a handy quick-reference tool to assist data professionals in their work, aiding in data interpretation, modeling , and decision-making processes.

Data Scientist 52

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Pickl AI

SEPTEMBER 3, 2023

Anomaly Detection in Machine Learning: An approach to data analysis and Machine Learning called “anomaly detection,” also referred to as “outlier detection,” focuses on finding data points or patterns that considerably differ from what is considered to be “normal” or anticipated behaviour.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Algorithm 52

phData

MAY 12, 2023

In today’s data-driven world, industries across the board are turning to advanced tools and technologies to gain deeper insights and improve their decision-making processes. This is particularly true in the financial services sector, where accurate, real-time data analysis can be the key to success.

Data Warehouse 72

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IBM Journey to AI blog

JULY 6, 2023

Just as humans can learn through experience rather than merely following instructions, machines can learn by applying tools to data analysis. Machine learning works on a known problem with tools and techniques, creating algorithms that let a machine learn from data through experience and with minimal human intervention.

Machine Learning 60

Machine Learning Machine Learning Data Science Big Data 60

Towards AI

JULY 19, 2023

That post was dedicated to an exploratory data analysis while this post is geared towards building prediction models. Feel free to try other algorithms such as Random Forests, Decision Trees, Neural Networks, etc., among supervised models and k-nearest neighbors, DBSCAN, etc., among unsupervised models.

Machine Learning 40

Machine Learning Machine Learning K-nearest Neighbors Support Vector Machines 40

Pickl AI

FEBRUARY 4, 2024

Alteryx’s Capabilities Data Blending: Effortlessly combine data from multiple sources. Predictive Analytics: Leverage machine learning algorithms for accurate predictions. This makes Alteryx an indispensable tool for businesses aiming to glean insights and steer their decisions based on robust data.

Data Preparation 52

Data Preparation Tableau Data Visualization SQL 52

Pickl AI

APRIL 28, 2023

Here is the tabular representation of the same: Technical Skills Non-technical Skills Programming Languages: Python, SQL, R Good written and oral communication Data Analysis: Pandas, Matplotlib, Numpy, Seaborn Ability to work in a team ML Algorithms: Regression Classification, Decision Trees, Regression Analysis Problem-solving capability Big Data: (..)

Data Scientist 52

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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

Towards AI

APRIL 4, 2024

Created by the author with DALL E-3 Machine learning algorithms are the “cool kids” of the tech industry; everyone is talking about them as if they were the newest, greatest meme. Shall we unravel the true meaning of machine learning algorithms and their practicability?

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IBM Journey to AI blog

DECEMBER 20, 2023

Each type and sub-type of ML algorithm has unique benefits and capabilities that teams can leverage for different tasks. Instead of using explicit instructions for performance optimization, ML models rely on algorithms and statistical models that deploy tasks based on data patterns and inferences. What is machine learning?

Machine Learning 82

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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.

Clustering 52

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Mlearning.ai

MAY 23, 2023

Read the full blog here —  [link] Data Science Interview Questions for Freshers 1. What is Data Science? 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. What is the main advantage of sampling?

Data Science 52

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ODSC - Open Data Science

JANUARY 5, 2024

Scikit-learn A machine learning powerhouse, Scikit-learn provides a vast collection of algorithms and tools, making it a go-to library for many data scientists. Without this library, data analysis wouldn’t be the same without pandas, which reign supreme with its powerful data structures and manipulation tools.

Python 52

Python K-nearest Neighbors Data Science Data Visualization 52

Pickl AI

AUGUST 23, 2023

By extracting insights from these datasets, professionals can make more informed investment decisions, reducing the risk associated with emotional biases. Predictive Analytics One of the most remarkable aspects of Data Science in stock market analysis is its predictive capabilities.

Data Science 52

Data Science Machine Learning Machine Learning Algorithm 52

Heartbeat

FEBRUARY 8, 2023

Python packages such as Scikit-learn assist fundamental machine learning algorithms such as classification and regression, whereas Keras, Caffe, and TensorFlow enable deep learning. R is frequently used for statistical software development, data analysis, and data visualisation because it can handle large data sets with ease.

Natural Language Processing 52

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Mlearning.ai

FEBRUARY 15, 2023

This data shows promise for the binary classifier that will be built. Figure 4 Data Cleaning Conventional algorithms are often biased towards the dominant class, ignoring the data distribution. Figure 5 shows the methods used to perform these data preprocessing techniques.

Cross Validation 52

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Dataconomy

SEPTEMBER 1, 2023

Heart disease stands as one of the foremost global causes of mortality today, presenting a critical challenge in clinical data analysis. Leveraging hybrid machine learning techniques, a field highly effective at processing vast healthcare data volumes is increasingly promising in effective heart disease prediction.

Decision Trees 195

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Pickl AI

JULY 23, 2023

Big Data Big data refers to vast volumes of information that exceed the processing capabilities of traditional databases. Characterized by the three Vs: volume, velocity, and variety, big data poses unique challenges and opportunities. This step is crucial for eliminating inconsistencies and ensuring data integrity.

Analytics 52

Analytics Analytics Predictive Analytics Data Analysis 52

DagsHub

APRIL 21, 2024

MLOps helps these organizations to continuously monitor the systems for accuracy and fairness, with automated processes for model retraining and deployment as new data becomes available. This is the reason why data scientists need to be actively involved in this stage as they need to try out different algorithms and parameter combinations.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

Dataconomy

FEBRUARY 24, 2023

It could be anything from customer service to data analysis. Collect data: Gather the necessary data that will be used to train the AI system. This data should be relevant, accurate, and comprehensive. Choose the appropriate algorithm: Select the AI algorithm that best suits the problem you want to solve.

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