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Happy Songs to sing and dance⛅Positive songs that boost your energy

🌷Tracklist:
00:00 Mandrazo & Bianca - Unstoppable
03:26 Dj Goja x Magic Phase - Calm Down
06:25 Aqua Vibe, Pop Mage - Flowers
09:32 Pop Mage, JustCosplaySings - Cupid
12:23 Pop Mage, Sup I’m Bianca, ThatMikeGuy - As It Was
15:02 ThatMikeGuy, S.I.B, Pop Mage - Kill Bill
17:29 Aqua Vibe, Andreea Flavia, Pop Mage - Creepin'
20:48 Mandrazo, Pop Mage - Anti-Hero
23:52 Mandrazo, Pop Mage, Elise Jordan - Wrecking Ball
26:08 Pop Mage, Mandrazo - Sweet But Psycho
28:34 Mandrazo, Pop Mage - Another Love
32:16 Pop Mage - Apologize
35:11 Pop Mage, Mandrazo - Summertime Sadness
38:41 Pop Mage, Elise Jordan - Die For You
43:01 Pop Mage - Your Song
46:08 Mandrazo, Pop Mage - Call Out My Name
49:15 Pop Mage - Love On The Brain
52:57 Pop Mage, Mandrazo - Talking To The Moon
56:34 Mandrazo, Pop Mage - I like Me Better
59:45 Adrian, Pop Mage - Middle Of The Night

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🪕Welcome To Top Pop Collection, A Music Channel Dedicated To Bringing You The Best Of The Best Music Tracks
Listen on Spotify: https://lnk.to/goodmoodds

best songs of the decade 2010-2019 #2 ~nostalgia vibes mix ~2010s summer roadtrip

Help me to get 100.000 subs: https://www.youtube.com/channe....l/UCBepjMYiqtq_u4ZFO

you are on a roadtrip summer night while listening to these nostalgic songs by Flo Rida, Pitbull, Ke$ha, Carly Rae Jepsen, Taylor Swift, Katy Perry, Miley Cyrus, Avicii, Adele, Ellie Goulding and many more!

All of the tracks used in my youtube playlists are copyrighted music, so if you see ads in my videos, it's because youtube places them automatically based on copyright-owners needs, I have no control over it, so sorry about that. My channel is NOT a monetized channel. My only goal is sharing nostalgic, road trip music for everyone!

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⏱️ Timestamps
0:00 Introduction
2:45 Basic API Call
5:10 Structured Output
8:00 Using Tools
18:31 Memory and Retrieval
24:35 Building an AI Calendar Agent
34:59 Prompt Chaining
37:56 Routing Requests
41:57 Parallelization
46:18 Deploying Your AI Application

📌 Description
In this tutorial, we’ll cover everything you need to start building AI agents in pure Python. We’ll start with the essential building blocks and then dive into workflow patterns for more reliable systems. To follow along, basic Python skills are recommended, along with familiarity with the OpenAI SDK and an API key. I highly recommend cloning the GitHub repository so you can work through the code step by step. Watch me go through it first, then try it yourself to reinforce your understanding. I move quickly to cover a lot in 45 minutes, but you can always pause, rewind, or ask ChatGPT for help.

👋🏻 About Me
Hi! I'm Dave, AI Engineer and founder of Datalumina®. On this channel, I share practical tutorials that teach developers how to build production-ready AI systems that actually work in the real world. Beyond these tutorials, I also help people start successful freelancing careers. Check out the links above to learn more!

Dive with us into the enigmatic world of Artificial General Intelligence (AGI)! 🌐 From Microsoft's game-changing Gorilla AI 🦍, exhibiting human-like cognition, to the art of crafting an AGI's digital brain 🧠. Ever wondered how close we are to welcoming AGI into our daily lives? The answer might surprise you! Explore AGI's vast potential applications, from healthcare 🩺 to space 🚀, and the challenges that lie ahead. Ensure you're equipped for the tech revolution; hit like 👍, share, and subscribe 🔔 for a front-row seat to the future. Let's decode tomorrow, today! 🚀

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Announcement: New Book by Luis Serrano! Grokking Machine Learning. bit.ly/grokkingML
40% discount code: serranoyt

A friendly introduction to Bayes Theorem and Hidden Markov Models, with simple examples. No background knowledge needed, except basic probability.
Accompanying notebook:
https://github.com/luisguiserrano/hmm

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

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Learn how to build AI agents from scratch in this beginner-friendly tutorial!

Jan breaks down the complex world of AI agents into simple, understandable components and shows you how to create a fun "Santa's Helper" agent that researches toys and sends wish lists - all without writing a single line of code.

What you'll learn:
▶︎ Understanding AI agent components and architecture
▶︎ Setting up large language models (LLMs)
▶︎ Implementing agent memory systems
▶︎ Writing effective agent system prompts
▶︎ Connecting research and web search tools
▶︎ Automating email communications
▶︎ Testing and debugging agents
▶︎ Real-world business applications

⏰ TIMESTAMPS
00:00 What are AI agents and how do they work
00:30 AI agent components and architecture explained
02:31 Understanding agent tools and capabilities
05:19 Building your first agent in n8n
06:30 Connecting language models to your agent
07:37 Why memory is crucial for AI agents
09:35 Creating effective system prompts for agents
12:08 Adding web search capabilities to agents
14:38 Setting up email automation tools
15:26 Testing and debugging your AI agent
18:22 Business use cases and advanced applications

📚 RESOURCES MENTIONED
https://www.youtube.com/watch?v=SzPE_AE0eEo
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💥 We’re launching the Modern Route-Full Stack Generative & Agentic AI Batch 💥
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Summary:
AI Agents seem overwhelming, but in 2026, we've gotten to the point that any non-technical person can create and manage their own AI agents to accomplish tasks. I cover everything simply: what an agent actually is, what to automate, how to start, and build two agents step by step using two of the leading platforms. Then dive into common pitfalls and how to avoid them. This is everything you need to get started with building AI agents in 2026, no coding required.

Chapters
0:00 Intro
0:50 What is an agent?
1:37 Where we're at right now
2:08 What to automate first
4:58 How to start
7:01 Time to build
7:24 Build 1
14:04 Build 2
20:43 More complex agents
22:03 Zapier vs n8n
22:40 Common Pitfalls (and how to avoid them)
24:44 The real skill

Learn how to use Dynamic Programming with Java in this course for beginners. It can help you solve complex programming problems, such as those often seen in programming interview questions about data structures and algorithms.

This course was developed by Alvin Zablan from Structy. Structy is a website for learning data structures and algorithms for technical interviews. Learn data structures and algorithms: https://structy.net/

Check out Alvin's channel: https://www.youtube.com/c/AlvinTheProgrammer

⭐️ Contents ⭐️
(0:00:00) course introduction
(0:01:38) fib
🔗 https://structy.net/problems/fib
(0:34:02) tribonacci
🔗 https://structy.net/problems/tribonacci
(0:47:05) sum possible
🔗 https://structy.net/problems/sum-possible
(1:04:18) min change
🔗 https://structy.net/problems/min-change
(1:22:22) count paths
🔗 https://structy.net/problems/count-paths
(1:39:02) max path sum
🔗 https://structy.net/problems/max-path-sum
(1:52:56) non adjacent sum
🔗 https://structy.net/problems/non-adjacent-sum
(2:08:22) summing squares
🔗 https://structy.net/problems/summing-squares
(2:21:50) counting change
🔗 https://structy.net/problems/counting-change

🎉 Thanks to our Champion and Sponsor supporters:
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👾 Otis Morgan
👾 Oscar Rahnama

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Learn how to build your own large language model, from scratch. This course goes into the data handling, math, and transformers behind large language models. You will use Python.

✏️ Course developed by @elliotarledge

💻 Code and course resources: https://github.com/Infatoshi/fcc-intro-to-llms

Join Elliot's Discord server: https://discord.gg/pV7ByF9VNm

⭐️ Contents ⭐️
(0:00:00) Intro
(0:03:25) Install Libraries
(0:06:24) Pylzma build tools
(0:08:58) Jupyter Notebook
(0:12:11) Download wizard of oz
(0:14:51) Experimenting with text file
(0:17:58) Character-level tokenizer
(0:19:44) Types of tokenizers
(0:20:58) Tensors instead of Arrays
(0:22:37) Linear Algebra heads up
(0:23:29) Train and validation splits
(0:25:30) Premise of Bigram Model
(0:26:41) Inputs and Targets
(0:29:29) Inputs and Targets Implementation
(0:30:10) Batch size hyperparameter
(0:32:13) Switching from CPU to CUDA
(0:33:28) PyTorch Overview
(0:42:49) CPU vs GPU performance in PyTorch
(0:47:49) More PyTorch Functions
(1:06:03) Embedding Vectors
(1:11:33) Embedding Implementation
(1:13:06) Dot Product and Matrix Multiplication
(1:25:42) Matmul Implementation
(1:26:56) Int vs Float
(1:29:52) Recap and get_batch
(1:35:07) nnModule subclass
(1:37:05) Gradient Descent
(1:50:53) Logits and Reshaping
(1:59:28) Generate function and giving the model some context
(2:03:58) Logits Dimensionality
(2:05:17) Training loop + Optimizer + Zerograd explanation
(2:13:56) Optimizers Overview
(2:17:04) Applications of Optimizers
(2:18:11) Loss reporting + Train VS Eval mode
(2:32:54) Normalization Overview
(2:35:45) ReLU, Sigmoid, Tanh Activations
(2:45:15) Transformer and Self-Attention
(2:46:55) Transformer Architecture
(3:17:54) Building a GPT, not Transformer model
(3:19:46) Self-Attention Deep Dive
(3:25:05) GPT architecture
(3:27:07) Switching to Macbook
(3:31:42) Implementing Positional Encoding
(3:36:57) GPTLanguageModel initalization
(3:40:52) GPTLanguageModel forward pass
(3:46:56) Standard Deviation for model parameters
(4:00:50) Transformer Blocks
(4:04:54) FeedForward network
(4:07:53) Multi-head Attention
(4:12:49) Dot product attention
(4:19:43) Why we scale by 1/sqrt(dk)
(4:26:45) Sequential VS ModuleList Processing
(4:30:47) Overview Hyperparameters
(4:32:14) Fixing errors, refining
(4:34:01) Begin training
(4:35:46) OpenWebText download and Survey of LLMs paper
(4:37:56) How the dataloader/batch getter will have to change
(4:41:20) Extract corpus with winrar
(4:43:44) Python data extractor
(4:49:23) Adjusting for train and val splits
(4:57:55) Adding dataloader
(4:59:04) Training on OpenWebText
(5:02:22) Training works well, model loading/saving
(5:04:18) Pickling
(5:05:32) Fixing errors + GPU Memory in task manager
(5:14:05) Command line argument parsing
(5:18:11) Porting code to script
(5:22:04) Prompt: Completion feature + more errors
(5:24:23) nnModule inheritance + generation cropping
(5:27:54) Pretraining vs Finetuning
(5:33:07) R&D pointers
(5:44:38) Outro

🎉 Thanks to our Champion and Sponsor supporters:
👾 davthecoder
👾 jedi-or-sith
👾 南宮千影
👾 Agustín Kussrow
👾 Nattira Maneerat
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👾 Serhiy Kalinets
👾 Justin Hual
👾 Otis Morgan

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🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐉𝐚𝐯𝐚 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠: https://www.edureka.co/java-j2ee-training-course (Use code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎")
This Edureka video on "Interface on Java" will provide you with detailed knowledge about Java Interface and also cover some real time examples in order to provide you a better understanding of the functionality of Java Interface. This video will cover the following topics:
00:00:00 Introduction
00:00:22 Agenda
00:00:56 What is an Interface?
00:01:30 Why do we need an Interface?
00:03:20 Practical examples on Interface
00:05:32 Interface Nesting
00:07:02 Difference between Class and Interface
00:08:30 Advantages and Disadvantages of Interface
00:09:10 Key Points on Interface.
00:09:55 Practical Examples of Interface on Key Points

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🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐜𝐞 𝐰𝐢𝐭𝐡 𝐏𝐲𝐭𝐡𝐨𝐧 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐮𝐫𝐬𝐞 : https://www.edureka.co/data-sc....ience-python-certifi (𝐔𝐬𝐞 𝐂𝐨𝐝𝐞: 𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎)
This Edureka video on 'How to become a Data Scientist' will give you an insight into why the data scientist job is in such a high demand. It then elaborates on different roles and responsibilities of a Data Scientist and what skills are required to fulfill those roles and responsibilities. Then, it build a roadmap that you can follow to become a Data Science Wizard (i.e. Data Scientist) and also it briefly provides you with a sense of how much time it takes to go through the roadmap. The video ends with some incredibly useful resources and courses to help you achieve your goal of becoming a Data Scientist.
00:00:00 Introduction
00:00:20 Agenda
00:00:49 What is Data Science
00:02:47 Why data science in 2020
00:03:40 Data Science Life Cycle
00:05:55 Learning Path for Data Science
00:18:25 How Edureka helps you Master Data Science?

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