Analytics Vidhya

NOVEMBER 29, 2021

This article was published as a part of the Data Science Blogathon. In this article, we will learn about model explainability and the different ways to interpret a machine learning model. What is Model Explainability? The post An End-to-End Guide to Model Explainability appeared first on Analytics Vidhya.

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IBM Journey to AI blog

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? What is machine learning?

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IBM Journey to AI blog

AUGUST 11, 2023

Because ML is becoming more integrated into daily business operations, data science teams are looking for faster, more efficient ways to manage ML initiatives, increase model accuracy and gain deeper insights. MLOps is the next evolution of data analysis and deep learning.

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NYU Center for Data Science

NOVEMBER 9, 2023

Yann LeCun is a renowned deep learning pioneer and one of the most important minds in AI, and over the past few years he has been developing a comprehensive theory of machine learning, centered around “energy-based models,” which he calls “the only way to formalize and understand all model types.”

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Analytics Vidhya

MAY 14, 2023

Thus, understanding the disparity between two fundamental algorithms, Regression vs Classification, becomes essential. […] The post Regression vs Classification in Machine Learning Explained! appeared first on Analytics Vidhya.

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Becoming Human

JANUARY 23, 2023

Data Science You heard this term most of the time all over the internet, as well this is the most concerning topic for newbies who want to enter the world of data but don’t know the actual meaning of it. I’m not saying those are incorrect or wrong even though every article has its mindset behind the term ‘ Data Science ’.

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Heartbeat

FEBRUARY 21, 2024

Photo by Almos Bechtold on Unsplash Deep learning is a machine learning sub-branch that can automatically learn and understand complex tasks using artificial neural networks. Deep learning uses deep (multilayer) neural networks to process large amounts of data and learn highly abstract patterns.

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Heartbeat

NOVEMBER 14, 2023

It has an excellent reputation as a tool for predicting many kinds of problems in data science and machine learning. For many years, gradient-boosting models and deep-learning solutions have won the lion's share of Kaggle competitions. In our next article, we can try an implementation of the model.

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ODSC - Open Data Science

OCTOBER 17, 2023

But without a strong understanding of deep learning, you’ll have a difficult time getting the most out of the cutting-edge developments in the industry. At ODSC West this October 30th to November 2nd, you’ll build the core knowledge and skills you need with the sessions in the deep learning track , such as the ones listed below.

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NYU Center for Data Science

JANUARY 18, 2024

Micah Goldblum , a Postdoctoral Researcher at CDS, has created exactly that, in a recent survey intended to capture the multifaceted views of influential figures in deep learning. Goldblum’s work, the first in a planned series, aims to document diverse opinions in the field, particularly those not amplified by social media platforms.

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Heartbeat

NOVEMBER 27, 2023

Deep learning automates and improves medical picture analysis. Convolutional neural networks (CNNs) can learn complicated patterns and features from enormous datasets, emulating the human visual system. Convolutional Neural Networks (CNNs) Deep learning in medical image analysis relies on CNNs.

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Heartbeat

OCTOBER 11, 2023

A key component of artificial intelligence is training algorithms to make predictions or judgments based on data. This process is known as machine learning or deep learning. Two of the most well-known subfields of AI are machine learning and deep learning. What is Deep Learning?

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Analytics Vidhya

AUGUST 26, 2021

This article was published as a part of the Data Science Blogathon “You can have data without information but you cannot have information without data” – Daniel Keys Moran Introduction If you are here then you might be already interested in Machine Learning or Deep Learning so I need not explain what it is?

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Pickl AI

FEBRUARY 12, 2024

Data Science interviews are pivotal moments in the career trajectory of any aspiring data scientist. Having the knowledge about the data science interview questions will help you crack the interview. Data Science skills that will help you excel professionally.

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Heartbeat

NOVEMBER 29, 2023

Two names stand out prominently in the wide realm of deep learning: TensorFlow and PyTorch. These strong frameworks have changed the field, allowing researchers and practitioners to create and deploy cutting-edge machine learning models. TensorFlow and PyTorch present distinct routes to traverse.

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Heartbeat

OCTOBER 18, 2023

In this article, we embark on a journey to explore the transformative potential of deep learning in revolutionizing recommender systems. However, deep learning has opened new horizons, allowing recommendation engines to unravel intricate patterns, uncover latent preferences, and provide accurate suggestions at scale.

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Pickl AI

NOVEMBER 3, 2023

Learning Data Science from YouTube is a flexible, cost-effective, and accessible way to gain knowledge and skills in this rapidly growing field. Data Science , one of the most talked about topics, has been garnering a lot of attention these days. Top Data Science YouTubers 1.

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Marktechpost

MAY 5, 2024

It covers topics such as clustering, predictive modeling, and advanced methods like ensemble learning using the scikit-learn toolkit. Participants also gain hands-on experience with open-source frameworks and libraries like TensorFlow and Scikit-learn. and demonstrates their application in various real-world applications.

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Heartbeat

SEPTEMBER 13, 2023

Source: ResearchGate Explainability refers to the ability to understand and evaluate the decisions and reasoning underlying the predictions from AI models (Castillo, 2021). Explainability techniques aim to reveal the inner workings of AI systems by offering insights into their predictions. What is Explainability?

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Heartbeat

AUGUST 1, 2023

A World of Computer Vision Outside of Deep Learning Photo by Museums Victoria on Unsplash IBM defines computer vision as “a field of artificial intelligence (AI) that enables computers and systems to derive meaningful information from digital images, videos and other visual inputs [1].”

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Heartbeat

FEBRUARY 13, 2023

Before you go… If you liked this article and want to stay tuned with more exciting articles on Python & Data Science  — do consider becoming a medium member by clicking here [link]. In this way, the portion of the membership fee goes to me, which motivates me to write more exciting stuff on Python and Data Science.

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Heartbeat

JUNE 23, 2023

However, with the advent of deep learning, researchers have explored various neural network architectures to model and forecast time series data. In this post, we will look at deep learning approaches for time series analysis and how they might be used in real-world applications. Let’s dive in!

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Heartbeat

SEPTEMBER 27, 2023

Dealing with your memory constraints Photo by Ian Talmacs on Unsplash In the previous article , we discussed the possibility of having memory constraints when trying to get into deep learning. When working with deep learning, arrays might become larger than what could fit in memory.

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Heartbeat

OCTOBER 3, 2023

Conclusion This is the end of the two-part series on memory mapping, where I have given a comprehensive beginner tutorial on the best method for a deep learning dive. These methods are not limited to deep learning as we have acquired an understanding of binaries and how they could be used to store information.

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Pickl AI

MAY 24, 2023

To help you understand Python Libraries better, the blog will explain a Python Libraries for Data Science List which you can learn about. This may include for instance in Machine Learning, Data Science, Data Visualisation, image and Data Manipulation. What is a Python Library?

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Heartbeat

SEPTEMBER 7, 2023

In the ever-evolving landscape of machine learning and artificial intelligence, understanding and explaining the decisions made by models have become paramount. Enter Comet , that streamlines the model development process and strongly emphasizes model interpretability and explainability. Why Does It Matter?

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Heartbeat

MAY 23, 2023

As technology continues to improve exponentially, deep learning has emerged as a critical tool for enabling machines to make decisions and predictions based on large volumes of data. Edge computing may change how we think about deep learning. Standardizing model management can be tricky but there is a solution.

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Analytics Vidhya

OCTOBER 10, 2022

This article was published as a part of the Data Science Blogathon. Introduction In this article, we will create a Mask v/s No Mask classifier using CNN and Machine Learning Classifiers. We will learn everything from scratch, and I will explain every […].

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Analytics Vidhya

JUNE 22, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction This article aims to explain Convolutional Neural Network and how. The post Building a Convolutional Neural Network Using TensorFlow – Keras appeared first on Analytics Vidhya.

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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. Now comes the exciting part ….

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Analytics Vidhya

SEPTEMBER 16, 2022

Introduction Data science is a practical subject that the experts can best explain in the field. These sessions will enhance your domain knowledge and help you learn new […].

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Analytics Vidhya

JUNE 23, 2022

He is working as a Senior Data Scientist with the IT consulting and solutions firm Careem. He has more than ten years of extensive experience in the field of analytics and data science. He will be explaining […].

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Heartbeat

MARCH 28, 2023

A complete guide to building a deep learning project with PyTorch, tracking an Experiment with Comet ML, and deploying an app with Gradio on HuggingFace Image by Freepik AI tools such as ChatGPT, DALL-E, and Midjourney are increasingly becoming a part of our daily lives. These tools were developed with deep learning techniques.

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Unite.AI

NOVEMBER 6, 2023

Adaptability to Unseen Data: These models may not adapt well to real-world data that wasn’t part of their training data. Neural Network: Moving from Machine Learning to Deep Learning & Beyond Neural network (NN) models are far more complicated than traditional Machine Learning models.

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Applied Data Science

OCTOBER 25, 2021

How I learned to stop worrying and love the field This blog covers all the core themes to starting your career in data science: ? Based on current predictions (enabled by data science), this trend will continue, as more and more industries shift towards data-driven and automated solutions.

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Heartbeat

JANUARY 31, 2023

In deep learning, activation functions add non-linearity to the neural networks. By non-linearity, it refers to a situation where there is not a linear relationship between the input data and the output data that can be represented by a simple linear equation.

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Analytics Vidhya

SEPTEMBER 27, 2022

This article was published as a part of the Data Science Blogathon. ” In that blog, I have explained: how to create a dataset directory, train, test and validation dataset splitting, and training from scratch. This blog is […].

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