Towards AI

MARCH 10, 2025

Welcome back to the second tutorial in our series, Nuclei Detection and Fluorescence Quantification in Python. In this tutorial, we will focus on measuring the fluorescence intensity from the GFP channel, extracting relevant data, and performing a detailed analysis to derive meaningful biological insights.

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Analytics Vidhya

JANUARY 29, 2024

Introduction Machine learning has revolutionized the field of data analysis and predictive modelling. With the help of machine learning libraries, developers and data scientists can easily implement complex algorithms and models without writing extensive code from scratch.

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Marktechpost

NOVEMBER 11, 2024

Python has become the go-to language for data analysis due to its elegant syntax, rich ecosystem, and abundance of powerful libraries. Data scientists and analysts leverage Python to perform tasks ranging from data wrangling to machine learning and data visualization.

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Data Analysis Python Natural Language Processing Computer Vision 89

Marktechpost

APRIL 2, 2024

Python is a general-purpose programming language and is one of the most popular languages because of its versatility, ease of use, libraries, and active community. Moreover, with the exponential rise in the popularity of artificial intelligence (AI), which mainly uses Python, there is an increase in demand for it.

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Marktechpost

MAY 15, 2024

In the vast world of data science, countless tools are available to help analysts and researchers make sense of data and build powerful machine-learning models. Here are the ten great Python packages that can significantly enhance your workflow. Lux: Lux is like having a data analysis assistant.

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Marktechpost

MAY 5, 2024

Additionally, Python has emerged as the primary language for various ML tasks. This article outlines the top ML courses in Python, offering readers the opportunity to enhance their skill set, transition careers, and meet the expectations of recruiters. and evaluating the same.

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Machine Learning Python Neural Network Convolutional Neural Networks 117

AWS Machine Learning Blog

OCTOBER 24, 2024

Alternatives to Rekognition people pathing One alternative to Amazon Rekognition people pathing combines the open source ML model YOLOv9 , which is used for object detection, and the open source ByteTrack algorithm, which is used for multi-object tracking. pip install opencv-python ultralytics !pip cvtColor(frame, cv2.COLOR_RGB2BGR)

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Towards AI

JANUARY 24, 2025

Using machine learning techniques/algorithms, we would try to predict whether a patient has diabetes or not. For any machine learning prediction model building, from technology part we would require the following things: Python [link] Lab [link] [link] Kaggle is basically a hub of dataset for machine learning and data analysis.

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Artificial Corner

SEPTEMBER 27, 2024

Image made with Midjourney As we’ve seen in previous articles Python is the language of choice for AI. In this article, I present you the 4 stages to learn Python for AI & Machine Learning. This is why, in this article, we will see the Python stuff you need for AI and Machine Learning and discover what stage you’re in.

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Marktechpost

SEPTEMBER 25, 2024

Subgroup Discovery (SD) is a supervised machine learning method used for exploratory data analysis to identify relationships (subgroups) within a dataset relative to a target variable. Despite the effectiveness of SD and the range of algorithms available, only some Python libraries offer state-of-the-art SD tools.

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Pickl AI

AUGUST 27, 2024

Summary: Python simplicity, extensive libraries like Pandas and Scikit-learn, and strong community support make it a powerhouse in Data Analysis. It excels in data cleaning, visualisation, statistical analysis, and Machine Learning, making it a must-know tool for Data Analysts and scientists. Why Python?

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Data Analysis Python Machine Learning Data Mining 52

Analytics Vidhya

JULY 21, 2024

These tests allow data scientists to validate hypotheses, compare groups, identify relationships, and make predictions with confidence. Whether you’re analyzing customer behavior, optimizing algorithms, […] The post 5 Statistical Tests Every Data Scientist Should Know appeared first on Analytics Vidhya.

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Marktechpost

NOVEMBER 13, 2024

Data modeling and data analysis are two fundamental ideas in the contemporary field of data science that frequently overlap but are very different from one another. Anyone who works with data, whether they are an IT specialist, business analyst, or data scientist, must be aware of their distinctions.

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Analytics Vidhya

MAY 29, 2022

Introduction on RFM Analysis This article aims to take you through the important concept of Customer Segmentation using RFM Analysis and how it can be done using machine learning. The algorithms we will be using are RFM analysis and comparing it with the […].

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Artificial Corner

DECEMBER 12, 2024

Before we start with today’s article, I’d like to tell you about something that might be of interest to those interested in Python and data science. DataCamp has an incredible certification program that’s perfect for you: The Python Data Associate Certification.

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Artificial Corner

JANUARY 23, 2025

This is what I did when I started learning Python for data science. I checked the curriculum of paid data science courses and then searched all the stuff related to Python. I selected the best 4 free courses I took to learn Python for data science.

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Data Science Python Convolutional Neural Networks Natural Language Processing 95

Marktechpost

MARCH 31, 2024

Whether you’re a beginner, a seasoned data scientist, or someone interested in leveraging data in your work, our carefully selected list of top data science books for 2024 offers a comprehensive guide. The book also provides Python code to explain these concepts.

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IBM Journey to AI blog

OCTOBER 15, 2024

and Python, supported by a scaled-out workflow that analyzes the billions of data points generated over the NFL season. Personalized analysis at scale Closer to the consumer, a Node.js “team needs” application personalizes these grades specific to a user’s team every 10 minutes. Why did it take so long?

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Pickl AI

JANUARY 30, 2023

Hence for an individual who wants to excel as a data scientist, learning Python is a must. The role of Python is not just limited to Data Science. In fact, Python finds multiple applications. It’s a universal programming language that finds application in different technologies like AI, ML, Big Data and others.

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Marktechpost

JULY 7, 2024

These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more. You’ll learn to use training data to discover predictive relationships, train algorithms, and avoid overtraining with techniques like cross-validation.

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IBM Journey to AI blog

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

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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.

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Marktechpost

AUGUST 8, 2024

Mathematics is crucial in data science as it underpins algorithms and models used for data analysis and prediction. It helps understand data patterns, optimize solutions, and make informed decisions. It includes hypothesis testing, regression, network analysis, and time series modeling.

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ODSC - Open Data Science

FEBRUARY 24, 2023

There are many well-known libraries and platforms for data analysis such as Pandas and Tableau, in addition to analytical databases like ClickHouse, MariaDB, Apache Druid, Apache Pinot, Google BigQuery, Amazon RedShift, etc. These tools will help make your initial data exploration process easy.

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Pickl AI

MAY 30, 2024

Summary: The Data Science and Data Analysis life cycles are systematic processes crucial for uncovering insights from raw data. Quality data is foundational for accurate analysis, ensuring businesses stay competitive in the digital landscape. Automated systems can extract data from websites or applications.

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Marktechpost

OCTOBER 10, 2024

Data science is used to guide decision-making and influence business strategies. Key Components of Data Science Data Collection : Gathering raw data from various sources. Data Cleaning : Ensuring the data is usable and accurate. Data Analysis : Applying statistical methods to discover trends.

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Pickl AI

AUGUST 1, 2023

In this article, we will explore the concept of applied text mining in Python and how to do text mining in Python. Introduction to Applied Text Mining in Python Before going ahead, it is important to understand, What is Text Mining in Python? How To Do Text Mining in Python?

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Pickl AI

OCTOBER 14, 2024

Summary: This article explores different types of Data Analysis, including descriptive, exploratory, inferential, predictive, diagnostic, and prescriptive analysis. Introduction Data Analysis transforms raw data into valuable insights that drive informed decisions. What is Data Analysis?

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ODSC - Open Data Science

MAY 22, 2023

Training AI-Powered Algorithmic Trading with Python Dr. Yves J. Hilpisch | The AI Quant | CEO The Python Quants & The AI Machine, Adjunct Professor of Computational Finance This session will cover the essential Python topics and skills that will enable you to apply AI and Machine Learning (ML) to Algorithmic Trading.

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Marktechpost

JULY 21, 2024

Methods like GraphRAG, Vector, and Text2Cypher make sophisticated querying and perceptive data analysis possible, and they also show how the retrieved data is used to provide relevant responses. The Neo4j LLM Knowledge Graph Builder is an adaptable application with a Python FastAPI backend and a React-based front end.

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Marktechpost

MAY 10, 2024

Machine Learning for Finance in Python This course teaches how to use Python to predict stock values with machine learning. It explores various models like linear, xgboost, and neural networks to analyze stock data and make predictions.

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Marktechpost

DECEMBER 18, 2024

Kite Kite is an AI-driven coding assistant specifically designed to accelerate development in Python and JavaScript. However, its main limitation is the restricted language support, as it currently focuses on Python and JavaScript, which makes it less versatile compared to other tools that support a broader range of languages.

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Marktechpost

APRIL 24, 2024

ELI5 is a Python package that helps debug machine learning classifiers and explain their predictions. ELI5 also implements several algorithms for inspecting black-box models. This Python package includes a comprehensive set of algorithms covering different explanation dimensions and proxy explainability metrics.

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ODSC - Open Data Science

MARCH 8, 2025

With the rise of generative AI and large language models (LLMs), its easy to assume that traditional data analysis techniques, like time series modeling , have taken a backseat. After all, LLMs generate human-like text, solve coding problems, and even analyze dataso why should we still focus on timeseries?

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ODSC - Open Data Science

FEBRUARY 2, 2023

Just as a writer needs to know core skills like sentence structure, grammar, and so on, data scientists at all levels should know core data science skills like programming, computer science, algorithms, and so on. While knowing Python, R, and SQL are expected, you’ll need to go beyond that.

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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.

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Viso.ai

MAY 21, 2024

Data science is a multidisciplinary field that relies on scientific methods, statistics, and Artificial Intelligence (AI) algorithms to extract knowledgable and meaningful insights from data. At its core, data science is all about discovering useful patterns in data and presenting them to tell a story or make informed decisions.

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