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/
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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 Gen AI Full Course video by Simplilearn will help you learn everything about Generative AI (Gen AI). The Gen AI full Course will begin with an in-depth exploration of generative artificial intelligence and its applications. It starts with an explanation of what Gen AI is, followed by the evolution of AI and a detailed roadmap for mastering generative AI. The course highlights future AI trends, top AI technologies, and career opportunities in the field. It includes hands-on machine learning projects for practice and tutorials on LangChain, deep learning, and advanced AI concepts like transformers, LSTMs, and recurrent neural networks. Additional topics include OpenAI tools such as ChatGPT, SearchGPT, and Sora, along with benchmarking large language models (LLMs) and generative adversarial networks. Reinforcement learning and machine learning tutorials are also covered, culminating with interview questions to prepare learners for AI-related roles.

The Full course covers the following topics:

00:00:00 Introduction to Gen AI Full Course
00:00:45 What is Gen AI
00:11:17 Evolution of AI
00:21:39 Roadmap Gen AI
00:37:18 AI Trends for the Fututre
00:37:59 Top 10 AI Technologies
00:47:50 AI Carrers
00:55:05 ML Projects For Practice
01:15:06 Wht is Langchain
01:34:03 Deep Learning Tutorial For Beginners
01:49:27 Open ai chatgpt o1 model
01:57:44 Search GPT
02:08:40 Openai sora
02:17:33 LLM Benchmarkeing
03:02:10 Generative Adversarial Tutorial
03:08:22 LSTM
03:09:23 Transformers in AI
03:17:04 Introduction to LLM
04:18:17 What is Machine Learning
05:14:49 Machine Learning Tutorial
07:20:12 Reinforcement Learning
08:49:51 Recurrent Neural Network
09:09:42 CHatgpt analyse
09:21:49 MAchine Learning Interview questions

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#genai #generativeai #artificialintelligence #ai #machinelearning #llm #simplilearn #2025

➡️ About Professional Certificate Program in Generative AI and Machine Learning

Dive into the future of AI with our Generative AI & Machine Learning course, in collaboration with E&ICT Academy, IIT Guwahati. Learn tools like ChatGPT, OpenAI, Hugging Face, Python, and more. Join masterclasses led by IITG faculty, engage in hands-on projects, and earn Executive Alumni Status.

Key Features:
✅ Program completion certificate from E&ICT Academy, IIT Guwahati
✅ Curriculum delivered in live virtual classes by seasoned industry experts
✅ Exposure to the latest AI advancements, such as generative AI, LLMs, and prompt engineering
✅ Interactive live-virtual masterclasses delivered by esteemed IIT Guwahati faculty
✅ Opportunity to earn an 'Executive Alumni Status' from E&ICT Academy, IIT Guwahati
✅ Eligibility for a campus immersion program organized at IIT Guwahati
✅ Exclusive hackathons and “ask-me-anything” sessions by IBM
✅ Certificates for IBM courses and industry masterclasses by IBM experts
✅ Practical learning through 25+ hands-on projects and 3 industry-oriented capstone projects
✅ Access to a wide array of AI tools such as ChatGPT, Hugging Face, DALL-E 2, Midjourney and more
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Skills Covered:
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✅ Prompt Engineering
✅ Chatbot Development
✅ Supervised and Unsupervised Learning
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✅ Model Evaluation and Validation
✅ Ensemble Methods
✅ Deep Learning
✅ Natural Language Processing
✅ Computer Vision
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✅ Python for Data Science (IBM)
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✅ Machine Learning
✅ Deep Learning with TensorFlow (IBM)
✅ Deep Learning Specialization
✅ Essentials of Generative AI, Prompt Engineering & ChatGPT
✅ Advanced Generative AI
✅ Capstone
Electives:
✅ ADL & Computer Vision
✅ NLP and Speech Recognition
✅ Reinforcement Learning
✅ Academic Masterclass
✅ Industry Masterclass

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This Claude Code Tutorial teaches you what I wish I knew as a software developer about Claude Code before I started AI coding. Get started here: https://clau.de/kevinstratvert

You can vibe code with other tools, or you can build durable software with tools like Claude Code. First, I'll walk you through how to install it on Mac or Windows.

Next, you’ll connect Claude Code to VS Code and learn how to build your first app - including how best to structure your prompts and what details are useful for Claude to know.

You'll review Claude's Plan mode like a senior engineer and learn how to work faster once you trust the changes it makes.

Next, you'll learn how to use Claude Code with an existing codebase - focusing on how to get it to analyze your coding standards so future changes are consistent. (Heavy use of CLAUDE.md)

Finally, you’ll execute a major architecture change and learn how best to work with Claude Code throughout the process.

Host: David DeWinter
Sponsor: Anthropic

📚 RESOURCES
Commands and Prompts to Copy ➜ https://drive.google.com/drive..../folders/1ZFRZcOCfep
CLAUDE.md guidance ➜ http://humanlayer.dev/blog/wri....ting-a-good-claude-m
Claude Code Best Practices by Anthropic ➜ https://www.anthropic.com/engi....neering/claude-code-

⌚ TIMESTAMPS
0:00 - Install Claude Code
2:08 - Create New App
7:56 - Existing App
11:48 - Architecture Change
14:31 - Your Next Steps

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#stratvert #claudeai

Presented at Code w/ Claude by @anthropic-ai on May 22, 2025 in San Francisco, CA, USA.

Speakers:
Cal Rueb, Member of Technical Staff at @anthropic-ai

The Intelligent Inspection toolset, powered by Deep Learning technology, provides powerful and robust on-device anomaly detection as well as object classification that is not possible with rule-based machine vision.

The user-friendly interface, on-device traning and example-based approach makes it easy to ensure that inspected items fulfill required quality and sorting demands, which helps to improve yield, reliability, productivity and increase customer satisfaction.

Intelligent Inspection toolset is part of the SICK Nova 2D SensorApp and runs directly on the InspectorP6xx 2D vision sensors.

And that’s not all, traditional rule-based machine vision tools are also included, combining benefits with deep learning side-by-side.

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This video on Project Management Professional covers all the concepts from basics to advanced. Also, it covers all the information about Project Management like what Project Management is ?, what is A Project ?, what are the Components of Project Management ?, What is A Project Life Cycle ?, and what are the Key Focus Areas in Project Management?

These are the facts we will be discussing in this video:
00:00 Introduction
01:34 What is Project Management?
02:38 What is A Project?
03:15 Components of Project Management
05:14 What is A Project Life Cycle?
09:10 Key Focus Areas in Project Management

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#WhatIsPMP #PMP #ProjectManagementProfessional #ProjectManagement #LearnProjectManagement #PMPCertification #Simplilearn

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The PMP certification is the global gold standard for project management professionals. Keep abreast of the changes in the project management practices updated in the PMBOK guide - 6th edition and pass the PMP® exam on your first attempt with Simplilearn’s new PMP course. The course covers new trends, emerging practices, and tailoring considerations, and places a greater emphasis on strategic and business knowledge. It also includes a new section on the role of the project manager.

PMP Certification Course Overview
The course covers new trends, emerging practices, tailoring considerations, and core competencies required of a Project Management professional. Placing a greater emphasis on strategic and business knowledge, this course also includes a new section on the role of the project manager in both large and small companies.

PMP Course Key Features:
- 35 contact hours/PDUs
- 8 industry case studies, 20 industry-based scenarios
- 6 hands-on projects, 7 simulation test papers (200 questions each)

Eligibility:
The PMP® certification is an essential professional requirement for senior project manager roles across all industries. The course is best suited for: Project Managers, Associate/Assistant Project Managers, Team Leads/Team Managers, Project Executives/Project Engineers, Software Developers, and Any professional aspiring to be a Project Manager.

Pre-requisites:
You should have a secondary degree (i.e. high school diploma, associate’s degree, or the global equivalent) with 7,500 hours of leading and directing projects along with 35 hours of project management education. OR You should have a four-year degree with 4,500 hours of leading and directing projects along with 35 hours of project management education.

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Fine-tuning GPT-3.
In this video we demonstrate how to use APIs and audio to create prompts and completions that can be used to fine-tune Transformers such as GPT-3. We show how to use a News API with Python to extract news articles and create a dataset for training and fine-tuning models.

We explain what prompt and completion datasets are, and the role they play in natural language processing in fine-tuning transformers. We then discuss using video and audio streams to build data pipelines for fine-tuning and transcribing speech to text using OpenAI's Whisper.

With over 500 hours of YouTube videos being uploaded every minute video is a rich source of detailed information with which to train AI.

The video first includes step-by-step demonstrations of using the News API to create a prompt and completion dataset and then shows how to build pipelines transcribing speech to text using Whisper.

Foundation models like GPT-3 can be 'Fine-Tuned'. This Fine_tuning allows them to learn the vocabulary and semantics of particular disciplines. If you want your AI solution to be familiar with options pricing algorithms, then you can show it lots of options pricing papers. If you'd like your AI to be able to converse and write about monetary policy then you can expose it to policy papers, books on economic theory, central bank meeting minutes and news conferences.

You train transformer AI models in a particular way. You don't simply feed in a file containing the text of the book or article that you are using to train the AI. You break the text up into a series of "Prompts" and "Completions". Prompts are the beginning of a passage of text and completions are what follow a prompt.

In this post we leverage the breadth and depth of content on YouTube. We propose a strategy to use selected videos to train our AI language models. These videos are chosen because they are rich in expertise in an area we want to train our language model in. The example used in this video is to train our AI in monetary policy by studying content generated by the Federal Reserve. We devise a strategy to use speech to text transcription of YouTube videos. We use OpenAI's 'Whisper' to perform this transcription. We then break this text up into 'prompts' and completions to train our model.

Following this approach we can easily train our NLP models to have expertise in any field we choose.



#NLP #Python #FineTuning #AI #MachineLearning #NewsAPI #Whisper #Lucidate #chatgpt #gpt3 #gpt-3 #openai #whisper #openai-whisper

Links:
Attention Mechanism in Transformers: https://youtu.be/sznZ78HquPc Transformer playlist: https://youtube.com/playlist?l....ist=PLaJCKi8Nk1hwaMU
Federal reserve Description: https://youtu.be/lJTmCv2kKKs
FOMC Feb 2023 Press Conference: https://www.youtube.com/watch?v=3Iv4aCN0OOo&t=2s
Python code for Transcriber class: https://github.com/mrspiggot/p....rompts_and_completio

=========================================================================
Link to introductory series on Neural networks:
Lucidate website: https://www.lucidate.co.uk/blog/categ...

YouTube: https://www.youtube.com/playlist?list...

Link to intro video on 'Backpropagation':
Lucidate website: https://www.lucidate.co.uk/post/intro...

YouTube: https://youtu.be/8UZgTNxuKzY

'Attention is all you need' paper - https://arxiv.org/pdf/1706.03762.pdf

=========================================================================
Transformers are a type of artificial intelligence (AI) used for natural language processing (NLP) tasks, such as translation and summarisation. They were introduced in 2017 by Google researchers, who sought to address the limitations of recurrent neural networks (RNNs), which had traditionally been used for NLP tasks. RNNs had difficulty parallelizing, and tended to suffer from the vanishing/exploding gradient problem, making it difficult to train them with long input sequences.

Transformers address these limitations by using self-attention, a mechanism which allows the model to selectively choose which parts of the input to pay attention to. This makes the model much easier to parallelize and eliminates the vanishing/exploding gradient problem.

Self-attention works by weighting the importance of different parts of the input, allowing the AI to focus on the most relevant information and better handle input sequences of varying lengths. This is accomplished through three matrices: Query (Q), Key (K) and Value (V). The Query matrix can be interpreted as the word for which attention is being calculated, while the Key matrix can be interpreted as the word to which attention is paid. The eigenvalues and eigenvectors of these matrices tend to be similar, and the product of these two matrices gives the attention score.

=========================================================================

#ai #deeplearning #chatgpt #gpt3 #neuralnetworks #attention #attentionisallyouneed

🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐂𝐨𝐮𝐫𝐬𝐞 - 𝐁𝐞𝐠𝐢𝐧𝐧𝐞𝐫𝐬 𝐭𝐨 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝: https://www.edureka.co/openai-....chatgpt-training-cou
In this Edureka video on 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐓𝐮𝐭𝐨𝐫𝐢𝐚𝐥 𝐟𝐨𝐫 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫𝐬, you will learn how to use ChatGPT for coding and programming using different languages. ChatGPT can become a very. useful tool for every developer.
00:00:00 ChatGPT for Developers
00:00:40 What is ChatGPT
00:01:37 How ChatGPT Works
00:02:16 ChatGPT vs Codex
00:03:16 How to use ChatGPT
00:03:51 ChatGPT for Programming
00:04:06 ChatGPT for Shell Scripting
00:08:45 ChatGPT for Python Programming
00:10:47 ChatGPT for HTML and CSS Coding
00:12:10 ChatGPT for JavaScript

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Welcome to our in-depth tutorial on Ethical HackerGPT! In this video, we'll explore HackerGPT, a specialized version of ChatGPT designed specifically for cybersecurity and ethical hacking. With cyberattacks occurring every 39 seconds and causing billions in damages, HackerGPT provides crucial tools and knowledge to protect against these threats. Discover how HackerGPT can guide you through a variety of topics, including performing security assessments, ethical hacking techniques, and scripting for system security. HackerGPT adheres strictly to ethical guidelines, ensuring all guidance aligns with legal and professional standards. Learn how to become a skilled cybersecurity professional, equipped to defend against cyber threats ethically and effectively. Join us for this engaging and informative tutorial, and enhance your cybersecurity skills with HackerGPT.

Here in this Ethical HackerGPT Tutorial, we cover the following topics:

00:00 Introduction to Cyber Security
02:10 Exploring Ethical Hacker GPT
04:33 Asking General Cybersecurity prompts from Ethical HackerGPT
06:05 Asking Ethical Hacking prompts from Ethical HackerGPT
07:33 Asking Scripting and Automation prompts from Ethical HackerGPT
09:39 Asking Specific Security Tools prompts from Ethical HackerGPT
10:47 Asking Incident Response prompts from Ethical HackerGPT
12:40 Asking Advanced Topics prompts from Ethical HackerGPT
15:55 Asking Cybersecurity Policies and Compliance prompts from Ethical HackerGPT

FAQs

1. What is HackerGPT and how does it work?
HackerGPT is a specialized version of ChatGPT designed for cybersecurity and ethical hacking. It provides guidance on a wide range of security topics, including vulnerability assessments, ethical hacking techniques, and scripting for system security. HackerGPT helps users understand and mitigate potential cyber threats while adhering to legal and ethical guidelines.

2. How can HackerGPT help improve my cybersecurity skills?
HackerGPT offers expert advice and practical solutions for various cybersecurity challenges. It covers topics such as security assessments, ethical hacking, scripting for automation, and using security tools like Burp Suite and Nmap. This guidance helps users enhance their knowledge and skills in defending against cyber threats.

3. Is HackerGPT safe and ethical to use?
Yes, HackerGPT is designed to follow strict ethical guidelines. It does not provide assistance for any queries deemed unethical or illegal. Its purpose is to help users learn and practice cybersecurity techniques responsibly, ensuring all guidance aligns with legal and professional standards.

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#HackerGPT #hacker #cybersecurity #EthicalHacking #Hacking #2024 #simplilearn

⏩ Check out the Cybersecurity videos: https://youtube.com/playlist?l....ist=PLEiEAq2VkUUJfPO

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MIT Introduction to Deep Learning 6.S191: Lecture 2
Recurrent Neural Networks
Lecturer: Ava Amini
** New 2024 Edition **

For all lectures, slides, and lab materials: http://introtodeeplearning.com

Lecture Outline
0:00​ - Introduction
3:42​ - Sequence modeling
5:30​ - Neurons with recurrence
12:20 - Recurrent neural networks
14:08 - RNN intuition
17:14​ - Unfolding RNNs
19:54 - RNNs from scratch
22:41 - Design criteria for sequential modeling
24:24 - Word prediction example
31:50​ - Backpropagation through time
33:40 - Gradient issues
37:15​ - Long short term memory (LSTM)
40:00​ - RNN applications
44:00- Attention fundamentals
46:46 - Intuition of attention
49:13 - Attention and search relationship
51:22 - Learning attention with neural networks
57:45 - Scaling attention and applications
1:00:08 - Summary
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1 Theme from A Summer Place - Percy Faith
2 He'll Have to Go - Jim Reeves
3 Cathy's Clown - The Everly Brothers
4 Running Bear - Johnny Preston
5 Teen Angel - Mark Dinning
6 I'm Sorry - Brenda Lee
7 It's Now or Never - Elvis Presley
8 Handy Man - Jimmy Jones
9 Stuck on You - Elvis Presley
10 The Twist - Chubby Checker
11 Everybody's Somebody's Fool - Connie Francis
12 Wild One - Bobby Rydell
13 Greenfields - The Brothers Four
14 What in the World's Come Over You - Jack Scott
15 El Paso - Marty Robbins
16 Alley Oop - The Hollywood Argyles
17 My Heart Has a Mind of Its Own - Connie Francis
18 Sweet Nothin's - Brenda Lee
19 Itsy Bitsy Teenie Weenie Yellow Polka Dot Bikini - Brian Hyland
20 Only the Lonely - Roy Orbison
21 Where or When - Dion and the Belmonts
22 Sixteen Reasons - Connie Stevens
23 Puppy Love - Paul Anka
24 Why - Frankie Avalon
25 Walk, Don't Run - The Ventures
26 Save the Last Dance for Me - The Drifters
27 Baby (You've Got What It Takes) - Dinah Washington & Brook Benton
28 Sink the Bismarck - Johnny Horton
29 Chain Gang - Sam Cooke
30 Let It Be Me - The Everly Brothers

Sing's Best Songs - "Let me hear you sing!" Groove with all your favorite songs featuring Rosita (Reese Witherspoon), Meena (Tori Kelly), Gunter (Nick Kroll), Ash (Scarlett Johansson), Johnny (Taron Egerton), and more! What's your favorite song from the Sing movies?
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CREDITS:
TM & © Universal (2021)
Cast: Reese Witherspoon, Nick Kroll, Taron Egerton, Scarlett Johansson, Tori Kelly

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Rotten Tomatoes MOVIECLIPS is the largest collection of movie clips on the web. Here you will find unforgettable moments, scenes, and quotes from all your favorite films.

This is my 50 Claude Code tips from 6 months of daily use personally and at Meta as a Staff Software Engineer. I've been coding with Claude Code basically 12 hours a day really trying to understand what makes Claude Code tik. Here's everything I wish I knew when I started, from foundations to advanced parallel workflows.

⏱️ TIMESTAMPS
0:00 - Intro
1:04 - ACT 1: Foundations (Tips 1-25)
1:18 - Tip 1: Run from root directory
1:56 - Tip 2: Run /init immediately
2:54 - Tip 3: CLAUDE.md is hierarchical
3:27 - Tip 4: Keep CLAUDE.md concise
3:58 - Tip 5: Structure: What, Domain, Validation
5:36 - Keyboard Shortcuts
5:58 - Tip 6: Shift+Tab toggles modes
6:40 - Tip 7: Escape interrupts
7:43 - Tip 8: Double Escape clears input
7:59 - Tip 9: Double Escape on empty = rewind
8:29 - Tip 10: Screenshot and drag
8:44 - Tip 11: Add context to screenshots
9:09 - Essential Commands
9:41 - Tip 12: /clear resets context
10:13 - Tip 13: /context shows token usage
11:42 - Tip 14: Let auto-compaction work
12:23 - Tip 15: /model switches models
12:49 - Tip 16: /resume recovers sessions
13:21 - Tip 17: /mcp shows MCP status
14:19 - Tip 18: /help shows all commands
14:33 - Tip 19: Git is your safety net
15:24 - CLAUDE.md Deep Dive
15:52 - Tip 20: Add a Critical Rules section
17:08 - Tip 21: Ask Claude to update rules
17:46 - Tip 22: Use workflow triggers
18:27 - Tip 23: Commit CLAUDE.md to git
19:34 - Tip 24: dangerously-skip for throwaway envs
20:39 - Tip 25: Combine skip with allowlists
20:59 - ACT 2: Daily Workflow (Tips 26-32)
21:38 - Tip 26: Start features in Plan Mode
23:46 - Tip 27: Fresh context beats bloated
24:29 - Tip 28: Persist before ending sessions
25:03 - Tip 29: Lazy load context
26:09 - Tip 30: Give verification commands
27:32 - Tip 31: Consider Opus for complex work
28:18 - Tip 32: Read thinking blocks
29:01 - ACT 3: Power User (Tips 33-40)
29:34 - Tip 33: Four composability primitives
29:54 - Tip 34: Skills = recurring workflows
31:33 - Tip 35: Commands = quick shorthand
32:18 - Tip 36: Never create commands manually
33:02 - Tip 37: MCPs = external service docs
33:52 - Tip 38: Ask Claude to install MCPs
34:15 - Tip 39: Subagents = isolated context
37:10 - Tip 40: Avoid instruction overload
37:48 - ACT 4: Advanced (Tips 41-50)
38:02 - Tip 41: Run multiple instances
39:06 - Tip 42: iTerm split panes
40:33 - Tip 43: Enable notifications
41:10 - Tip 44: Git worktrees for isolation
41:40 - Tip 45: /chrome connects browser
43:17 - Tip 46: Powerful for debugging
43:28 - Hooks & Automation
43:41 - Tip 47: Hooks intercept actions
44:10 - Tip 48: Auto-format with PostToolUse
44:24 - Tip 49: Block dangerous commands
44:43 - Tip 50: Explore the plugin ecosystem
45:32 - Context is King (Outro)

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Sebastian's books: https://sebastianraschka.com/books/
The lecture slides are available at: https://github.com/rasbt/stat4....53-deep-learning-ss2

Covers some of the basics of recurrent neural networks. In particular, this lecture covers

RNNs and Sequence Modeling Tasks: 00:00
Backpropagation Through Time: 20:23
Long-short term memory (LSTM): 31:42
Many-to-one Word RNNs: 45:16
Generating Text with Character RNNs: 50:45
Attention Mechanisms and Transformers: 1:00:09

Enroll today at https://www.coursera.org/speci....alizations/deep-lear to get access to the specialization!


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