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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Marktechpost

MARCH 31, 2024

As we enter 2024, the field of data science continues to evolve rapidly, making it essential to stay updated with the latest knowledge and trends. Practical Statistics for Data Scientists This is a beginner-friendly book that covers the statistical concepts that are essential for the field of data science.

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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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Analytics Vidhya

MAY 5, 2024

7B Explained appeared first on Analytics Vidhya. It is designed for a variety of code and natural language generation tasks. The 7B model is part of the Gemma family and is further trained on more than 500 billion tokens […] The post Is Coding Dead? Google’s CodeGemma 1.1

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Pickl AI

SEPTEMBER 23, 2024

Summary: This guide covers the most important Deep Learning interview questions, including foundational concepts, advanced techniques, and scenario-based inquiries. Gain insights into neural networks, optimisation methods, and troubleshooting tips to excel in Deep Learning interviews and showcase your expertise.

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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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Pickl AI

AUGUST 23, 2024

Summary: This blog post delves into the importance of explainability and interpretability in AI, covering definitions, challenges, techniques, tools, applications, best practices, and future trends. It focuses on providing insights into why a model produced a specific output based on its input data.

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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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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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The MLOps Blog

NOVEMBER 14, 2023

Deep learning models are typically highly complex. While many traditional machine learning models make do with just a couple of hundreds of parameters, deep learning models have millions or billions of parameters. The reasons for this range from wrongly connected model components to misconfigured optimizers.

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Pickl AI

JUNE 9, 2024

Summary: Mastering mathematics is crucial for excelling in Data Science. Overcoming challenges through practical applications, continuous learning, and resource utilisation is key to success. Introduction Mathematics plays a pivotal role in Data Science.

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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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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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Heartbeat

AUGUST 29, 2023

Deep learning is a branch of machine learning that makes use of neural networks with numerous layers to discover intricate data patterns. Deep learning models use artificial neural networks to learn from data. It is a tremendous tool with the ability to completely alter numerous sectors.

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Mlearning.ai

DECEMBER 13, 2023

Mastering Deep Learning and AI Interview Questions: What You Need to Know Image created by the author on Canva Knowledge is power, but enthusiasm pulls the switch.” Ever wondered what it takes to excel in deep learning interviews? Explain the vanishing and exploding gradient problems. said Ivern Ball.

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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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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

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

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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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 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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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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ODSC - Open Data Science

APRIL 19, 2023

Deep learning continues to be a hot topic as increased demands for AI-driven applications, availability of data, and the need for increased explainability are pushing forward. So let’s take a quick dive and see some big sessions about deep learning coming up at ODSC East May 9th-11th.

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Pickl AI

OCTOBER 8, 2024

Summary: This blog discusses Explainable Artificial Intelligence (XAI) and its critical role in fostering trust in AI systems. One of the most effective ways to build this trust is through Explainable Artificial Intelligence (XAI). What is Explainable AI (XAI)? What is Explainable AI (XAI)?

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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

JANUARY 15, 2023

With the speedy evolution of technologies, Machine Learning, Artificial Intelligence and Deep learning meaning might baffle you. This blog would act as a guide for you to understand the concept- What is Deep Learning?- and how it works in the Data Science field. What is Deep Learning in AI?

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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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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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Data Science Python Deep Learning Data Scientist 94

Unite.AI

APRIL 9, 2024

These techniques include Machine Learning (ML), deep learning , Natural Language Processing (NLP) , Computer Vision (CV) , descriptive statistics, and knowledge graphs. Key benefits include: reducing the necessity of large data science teams. Combining diverse AI techniques enables human-like decision-making.

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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

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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Pickl AI

JULY 1, 2024

Demand forecasting, powered by data science, helps predict customer needs. Optimize inventory, streamline operations, and make data-driven decisions for success. Learn the methods and techniques to forecast like a pro! Ensemble Learning Combine multiple forecasting models (e.g.,

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Heartbeat

APRIL 23, 2023

Photo by RetroSupply on Unsplash Introduction Deep learning has been widely used in various fields, such as computer vision, NLP, and robotics. The success of deep learning is largely due to its ability to learn complex representations from data using deep neural networks.

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Heartbeat

MAY 2, 2023

Artificial intelligence has undergone a revolution thanks to deep learning. Deep learning allows machines to learn from vast amounts of data and carry out complex tasks that were previously only considered possible by humans (like translation between languages, recognizing objects etc.).

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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

NOVEMBER 21, 2023

Computer vision, the field dedicated to enabling machines to perceive and understand visual data, has witnessed a monumental shift in recent years with the advent of deep learning. Photo by charlesdeluvio on Unsplash Welcome to a journey through the advancements and applications of deep learning in computer vision.

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ODSC - Open Data Science

NOVEMBER 19, 2024

ODSC West 2024 showcased a wide range of talks and workshops from leading data science, AI, and machine learning experts. This blog highlights some of the most impactful AI slides from the world’s best data science instructors, focusing on cutting-edge advancements in AI, data modeling, and deployment strategies.

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