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Self-attention and the transformer architecture have broken many benchmarks and enabled widespread progress in NLP. However, at this point neither researchers nor companies in industry (with a few exceptions) have leveraged them in a time series context. This talk will explore both the barriers and promise of self-attention models and transfer learning in a time series context. The talk will also look into why time series tasks (forecasting/prediction) have not had their BERT/Imagenet moment and what can be done to enable transfer learning on temporal data. The extremely limited COVID-19 time series forecasting dataset will be used as an example for the need to address these limited data scenarios and enable effective few-shot/transfer learning more generally.

Isaac Godfried is a machine learning engineer at Monster focusing on the data and machine learning platform. Prior to his current position Isaac worked on machine learning problems in both retail and healthcare. He also has participated in many Kaggle competitions. Isaac’s main focus is to remove barriers related to the use of deep learning in industry. Specifically, this involves researching techniques like transfer and meta learning for data constrained scenarios, designing tools to effectively track and manage experiments, and creating frameworks to deploy models at scale. In his spare time Isaac also conducts research in AI for good causes like medicine and climate.

👩🏼‍🚀Weights and Biases:
We’re always free for academics and open source projects. Email carey@wandb.com with any questions or feature suggestions.

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🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚'𝐬 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐂𝐨𝐮𝐫𝐬𝐞 (𝐔𝐬𝐞 𝐂𝐨𝐝𝐞: 𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎) :
https://www.edureka.co/microso....ft-azure-data-engine
This Edureka video on "Big Data Engineer Skills" will tell you the required skill sets to become a Big Data Engineer. It includes the following topics:
Who is a Big Data Engineer?
Big Data Engineer Responsibilities
Big Data Engineer Skills
How to acquire those skills?

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⏩ NEW Top 10 Technologies To Learn In 2023 - https://youtu.be/udD_GQVDt5g

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Ms. Coffee Bean explains how a huge collaboration of researchers managed to extract training data from large language models like GPT-2. Why is this even possible and what does this mean for even larger models like GPT-3?
Discussed paper:
" Extracting Training Data from Large Language Models" explained by Carlini et al. 2020.

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🔥 Optionally, pay us a coffee to boost our Coffee Bean production! ☕
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📺 GPT-3 – what you need to know: https://youtu.be/5fqxPOaaqi0

Outline:
* 00:00 Large Language Models
* 01:55 GPT-2
* 02:33 Why is it possible?
* 03:38 k-eidetic memorization
* 04:21 How does the attack work?
* 05:49 How bad is it?
* 08:12 What to do?

📄 Paper explained: Carlini, N., Tramer, F., Wallace, E., Jagielski, M., Herbert-Voss, A., Lee, K., ... & Oprea, A. (2020). Extracting Training Data from Large Language Models. arXiv preprint arXiv:2012.07805. https://arxiv.org/pdf/2012.07805.pdf

-------------------------------------------------------------
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In this video on Project Management Full Course, we shall begin learning the basics of project management. As we move forward, we shall verse ourselves with different project management concepts like project planning, project time, cost quality, and communication management. We will learn about project manager roles and different project management tools. Finally, in this project management tutorial for beginners, we shall see some Project Management interview questions to excel in any Project Management interview.
By the end of this course, you'll have everything you need to know about Project Management. So without further ado, let's jump in!
00:00 Project management full course - Introduction
02:05 What is project management?
12:28 Project lifecycle
34:41 Job roles and responsibility
39:30 Project management certifications
53:00 What is PMP?
01:05:00 Project management detailed guide
05:03:00 Trello Tutorial
06:25:33 Project manager interview questions and answers

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🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐀𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐚𝐥 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐮𝐫𝐬𝐞 : https://www.edureka.co/advance....d-artificial-intelli
This Edureka "Convolutional Neural Network Tutorial" video (Blog: https://goo.gl/4zxMfU) will help you in understanding what is Convolutional Neural Network and how it works. It also includes a use-case, in which we will be creating a classifier using TensorFlow.

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📝Feel free to share your comments below.📝

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

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Top 20 Most Important Excel Formulas by simplilearn is dedicated to guide the aspiring data analysts and business analysts with the top Excel Formulas For Data Analysis in 2024 and beyond. This Excel tutorial for beginners by Simplilearn will cover the following topics. In this video, we learn into the top 20 to 25 most important Excel formulas every data analyst needs to excel in their role.This excel tutorial will help you to refine your skills, and building a strong foundation in Excel proficiency.

0:00:00 How To Change Lower Case To Upper Case In Excel?
0:01:14 How To Add Rows In Excel?
0:02:47 How To Add Columns In Excel?
0:05:44 How To Select Entire Column In Excel?
0:08:32 How to Compare Two Columns In Excel?
0:15:51 How To Convert Rows To Columns In Excel?
0:17:28 How to Group Rows in Excel?
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0:23:00 How To Freeze Row In Excel Tutorial
0:25:29 How to Convert Number to Words in Excel?
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0:30:42 How To Merge Cells In Excel
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0:40:57 How To Calculate Age In Excel From A Date Of Birth?
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0:44:29 DAX In Excel Explained
0:49:34 Checkboxes In Excel
0:53:45 How to Insert Excel in PPT?
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1:02:46 How To Convert PDF To Excel

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➡️ About Post Graduate Program In Data Analytics
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Hi! I will be conducting one-on-one discussion with all channel members. Checkout the perks and Join membership if interested: https://www.youtube.com/channe....l/UCG04dVOTmbRYPY1wv Check membership Perks: https://www.youtube.com/channe....l/UCG04dVOTmbRYPY1wv
. In this video, I have explained what is meant by Deep Learning, Artificial Neural Networks and Applications of Deep Learning.

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Hi guys! I am Siddhardhan. I work in the field of Data Science and Machine Learning. It all started with my curiosity to learn about Artificial Intelligence and the ability of AI to solve several Real Life Problems. I worked on several Machine Learning & Deep Learning projects involving Computer Vision.
I am on this journey to empower as many students & working professionals as possible with the knowledge of Machine Learning and Artificial Intelligence.

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Thanks in advance!

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I am making a "Hands-on Machine Learning Course with Python" in YouTube. I'll be posting 3 videos per week. 2 videos on Machine Learning basics (Monday & Wednesday Evening). 1 video on a Machine Learning project (Friday Evening).

Download the Course Curriculum File from here: https://drive.google.com/file/....d/17i0c6SmncNuwSgr9W

LinkedIn: https://www.linkedin.com/in/si....ddhardhan-s-74165220

Telegram Group: https://t.me/siddhardhan

Facebook group: https://www.facebook.com/group....s/490857825649006/?r Instagram: https://www.instagram.com/siddhardhan23

Want to learn more? I’m hosting a 6-week live BootCamp for AI Builders.
👉 Save 40% on the New Years Cohort: https://maven.com/shaw-talebi/....ai-builders-bootcamp

This is the 6th video in a series on using large language models (LLMs) in practice. Here, I review key aspects of developing a foundation LLM based on the development of models such as GPT-3, Llama, Falcon, and beyond.

More Resources:
▶️ Series Playlist: https://www.youtube.com/playli....st?list=PLz-ep5RbHos Read more: https://towardsdatascience.com..../how-to-build-an-llm

[1] BloombergGPT: https://arxiv.org/pdf/2303.17564.pdf
[2] Llama 2: https://ai.meta.com/research/p....ublications/llama-2-
[3] LLM Energy Costs: https://www.statista.com/stati....stics/1384401/energy
[4] arXiv:2005.14165 [cs.CL]
[5] Falcon 180b Blog: https://huggingface.co/blog/falcon-180b
[6] arXiv:2101.00027 [cs.CL]
[7] Alpaca Repo: https://github.com/gururise/AlpacaDataCleaned
[8] arXiv:2303.18223 [cs.CL]
[9] arXiv:2112.11446 [cs.CL]
[10] arXiv:1508.07909 [cs.CL]
[11] SentencePience: https://github.com/google/sent....encepiece/tree/maste
[12] Tokenizers Doc: https://huggingface.co/docs/tokenizers/quicktour
[13] arXiv:1706.03762 [cs.CL]
[14] Andrej Karpathy Lecture: https://www.youtube.com/watch?v=kCc8FmEb1nY&t=5307s
[15] Hugging Face NLP Course: https://huggingface.co/learn/n....lp-course/chapter1/7
[16] arXiv:1810.04805 [cs.CL]
[17] arXiv:1910.13461 [cs.CL]
[18] arXiv:1603.05027 [cs.CV]
[19] arXiv:1607.06450 [stat.ML]
[20] arXiv:1803.02155 [cs.CL]
[21] arXiv:2203.15556 [cs.CL]
[22] Trained with Mixed Precision Nvidia: https://docs.nvidia.com/deeple....arning/performance/m
[23] DeepSpeed Doc: https://www.deepspeed.ai/training/
[24] https://paperswithcode.com/method/weight-decay
[25] https://towardsdatascience.com..../what-is-gradient-cl
[26] arXiv:2001.08361 [cs.LG]
[27] arXiv:1803.05457 [cs.AI]
[28] arXiv:1905.07830 [cs.CL]
[29] arXiv:2009.03300 [cs.CY]
[30] arXiv:2109.07958 [cs.CL]
[31] https://huggingface.co/blog/ev....aluating-mmlu-leader
[32] https://www.cs.toronto.edu/~hi....nton/absps/JMLRdropo

--
Homepage: https://shawhintalebi.com/
Book a call: https://calendly.com/shawhintalebi

Intro - 0:00
How much does it cost? - 1:30
4 Key Steps - 3:55
Step 1: Data Curation - 4:19
1.1: Data Sources - 5:31
1.2: Data Diversity - 7:45
1.3: Data Preparation - 9:06
Step 2: Model Architecture (Transformers) - 13:17
2.1: 3 Types of Transformers - 15:13
2.2: Other Design Choices - 18:27
2.3: How big do I make it? - 22:45
Step 3: Training at Scale - 24:20
3.1: Training Stability - 26:52
3.2: Hyperparameters - 28:06
Step 4: Evaluation - 29:14
4.1: Multiple-choice Tasks - 30:22
4.2: Open-ended Tasks - 32:59
What's next? - 34:31

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This Tableau Full Course Video by simplilearn is curated to help you learn the basics of tableau. This Simplilearn Tableau Full Course is designed to help you master the basics of Tableau and business analysis. The course starts with an introduction to Big Data and Business Analytics, followed by a guide to Power BI and creating dashboards in minutes. You'll explore key BI terms, Business Intelligence, and Business Analytics. Next, the course covers tools like Microsoft Power Query for data transformation. You'll also compare the roles of Data Analyst vs. Business Analyst, with tips on interview questions. Additionally, it includes boosting your skills with ChatGPT and Excel for data analytics. Finally, you'll dive into SQL for Business Analysis, complete practical SQL projects, and prepare for Business Analytics interview questions.

The course covers the following topics:

00:00:00 Introduction to Business Analysis
00:04:02 What is Big Data
01:11:17 introduction to Business analytics
01:17:12 Introduction to Power BI
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01:37:53 Create PowerBI Dashboard in minutes
01:46:41 Business Intelligence
07:06:24 Business Analytics
07:27:48 How to use microsoft power query
08:11:28 Data Analyst Vs Business Analyst
08:27:05 Chatgpt and Excel with Data Analytics
08:43:26 Data Transformation
08:46:43 SQL For Business Analysis
09:50:02 SQL Project Business Analysis
10:06:40 Business Analytics Interview Questions

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This Data Analytics Program is ideal for all working professionals and prior programming knowledge is not required. It covers topics like data analysis, data visualization, regression techniques, and supervised learning in-depth via our applied learning model with live sessions by leading practitioners and industry projects.

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Build your first AI agent without coding, check out Lindy: https://go.lindy.ai/ishan

In the past few months, the internet has been flooded with articles and videos about AI agents, highlighting how they simplify people's lives, maximize productivity, and even generate income.

I finally found a crazy AI tool that can help you build AI agents by just describing your idea through a simple text prompt. It has more than 1000 integrations, and it works with all your daily apps like Gmail, Google Calendar, Notion, Sheets, and even social media apps.

From email replier, meeting summariser, AI grammar assistant, to even writing social media posts for you, you can build agents for anything

It has lots of ready-to-use templates that you can try out and start building for free

The smartest people I know are already using AI agents like this to free up their time.

Watch the video till the end to learn about it in detail, and let me know in the comments what you are going to build with Lindy

📸 Instagram: https://bit.ly/ishansharma7390ig

Join MarkitUpX Discord Server: https://discord.gg/fwSpTje4rh

CHAPTERS:-
00:00 - Introduction
01:34 - Lindy interface
02:06 - Flow editor
09:51 - AI agent
11:38 - Examples of AI agents
15:49 - Conclusion

😁 About Me: https://bit.ly/aboutishansharma
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📝 LinkedIn: https://bit.ly/ishansharma7390li

🌟 Please leave a LIKE ❤️ and SUBSCRIBE for more AMAZING content! 🌟

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Learn how to design with Claude Code from Anthropic in real product workflows with Figma MCP.

I cover what Claude Code is, how designers can use it, and how to turn it into a serious productivity multiplier for UX exploration, documentation, prototyping, and shipping faster.

If you’re a UI, UX, or Product Designer looking to build better products, work smarter with AI, and stay competitive in a rapidly changing industry, this guide is for you.

🔗 KEY LINKS
📣 JOIN THE COMMUNITY: https://uicollective.co/
❎ Follow me on X: https://x.com/KirkMDesign

Why Join UI Collective Academy? Get access to premium courses, premium downloads, and so much more on the way (I am largely building this solo...trying to make design education available for all, support goes a long way!)

↪️ Need a design system? (also included in the academy): https://collectivekit.co/

🔗 VIDEOS TO WATCH
Build a Design System: https://youtu.be/opTANvl9G1g
Complex Design System Setup: https://youtu.be/L-tpK7Eeuow
AI & Design Systems: https://youtu.be/XfezMs8B-O8

🔗 MORE LINKS
Let us build or fix your design system: https://designsystemlabs.co/
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kirkland@uicollective.co

VIDEO LINKS & MORE:
Installation: https://code.claude.com/docs/en/overview#terminal
For installation: /plugin install figma@claude-plugins-official
MCP documentation: https://code.claude.com/docs/en/mcp
https://www.pencil.dev/

0:00 An Introduction
0:53 Introduction to Claude Code
3:23 Claude Code & Opus 4.6
4:26 Setting Up Claude Code
6:07 Connecting Figma MCP
7:35 Building a Figma Design with Claude Code
11:59 Claude Code Desktop App
13:32 Pencil App Demo
14:31 Building a Design with Claude Code & Pencil

MIT 18.156 Projection Theory, Spring 2025
Instructor: Lawrence D Guth
View the complete course: https://ocw.mit.edu/courses/18....-156-projection-theo
YouTube Playlist: https://www.youtube.com/playli....st?list=PLUl4u3cNGP6

We formulate the main questions and goals of the class, especially the exceptional set problem.

License: Creative Commons BY-NC-SA
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The imagedeep.io series serves to bridge the knowledge gap between medical imaging and AI education.

It was co-founded and is co-instructed by:

Mazen Zawaideh, MD. Chief Radiology Resident and imagedeep.io co-instructor.

David Haynor, MD, Ph.D. Professor of Neuroradiology and imagedeep.io co-instructor.

Nathan Cross, MD. Assistant Professor of Neuroradiology and imagedeep.io co-instructor.

To learn more, visit www.imagedeep.io