Best Of Arijit Singh 2024 | Arijit Singh Hits Songs | Arijit Singh Jukebox Songs | Indian Songs

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1. Helen Reddy - Angie Baby
2. John Denver - Annie's Song
3. Cat Stevens - Another Saturday Night
4. John Denver - Back Home Again
5. Paul McCartney & Wings - Band on the Run
6. First Class - Beach Baby
7. Elton John - Bennie and the Jets
8. Bo Donaldson & The Heywoods / Paper Lace - Billy Don't Be a Hero
9. Elton John - Candle in the Wind
10. Barry White - Can't Get Enough of Your Love
11. Gordon Lightfoot - Carefree Highway
12. Harry Chapin - Cat's in the Cradle
13. Redbone - Come and Get Your Love
14. Cher - Dark Lady
15. Suzi Quatro - Devil Gate Drive
16. Elton John - Don't Let the Sun Go Down on Me
17. Carl Carlton - Everlasting Love
18. Ken Boothe - Everything I Own
19. Slade - Far Far Away
20. Johnny Bristol - Hang On In There Baby
21. Paul Anka with Odia Coates - (You're) Having My Baby
22. Showaddywaddy - Hey Rock and Roll
23. ABBA / Sweet Dreams - Honey Honey
24. Blue Swede - Hooked on a Feeling
25. Billy Swan - I Can Help
26. Olivia Newton-John - I Honestly Love You
27. Eric Clapton - I Shot the Sheriff
28. Carpenters - I Won't Last a Day Without You
29. Terry Jacks - If You Go Away
30. Olivia Newton-John - If You Love Me (Let Me Know)
31. Jim Croce - I'll Have to Say I Love You in a Song
32. Albert Hammond - I'm a Train
33. Alvin Stardust - Jealous Mind
34. Paul McCartney & Wings - Jet
35. Dolly Parton - Jolene
36. The Rubettes - Jukebox Jive
37. Kool and the Gang - Jungle Boogie
38. Paul McCartney & Wings - Junior's Farm
39. Queen - Killer Queen
40. The Drifters - Kissin' in the Back Row
41. Carl Douglas - Kung Fu Fighting
42. Neil Sedaka - Laughter in the Rain
43. Bachman–Turner Overdrive - Let It Ride
44. Mud - Lonely This Christmas
45. Neil Diamond - Long Fellow Serenade
46. The Osmonds - Love Me for a Reason
47. The Love Unlimited Orchestra - Love's Theme
48. Elton John - Lucy in the Sky with Diamonds
49. Electric Light Orchestra - Ma-Ma-Ma-Belle
50. Maria Muldaur - Midnight at the Oasis
51. Bee Gees - Mr. Natural
52. Gloria Gaynor - Never Can Say Goodbye
53. Billy Preston - Nothing from Nothing
54. Cat Stevens - Oh Very Young
55. Billy Joel - Piano Man
56. Golden Earring - Radar Love
57. David Bowie - Rebel Rebel
58. Steely Dan - Rikki Don't Lose That Number
59. The Righteous Brothers - Rock and Roll Heaven
60. Andy Kim - Rock Me Gently
61. The Hues Corporation - Rock the Boat
62. George McCrae - Rock Your Baby
63. Sweet Sensation - Sad Sweet Dreamer
64. Terry Jacks - Seasons in the Sun
65. Queen - Seven Seas of Rhye
66. Bay City Rollers - Shang-a-Lang
67. Charles Aznavour - She
68. Al Wilson - Show and Tell
69. Blue Magic - Sideshow
70. Ralph McTell - Streets of London
71. The Rubettes - Sugar Baby Love
72. Bay City Rollers - Summerlove Sensation
73. Gordon Lightfoot - Sundown
74. John Denver - Sunshine on My Shoulders
75. Lynyrd Skynyrd - Sweet Home Alabama
76. The Sweet - Teenage Rampage
77. The Hollies - The Air That I Breathe
78. Slade - The Bangin' Man
79. Elton John - The Bitch Is Back
80. Mud - The Cat Crept In
81. Billy Joel - The Entertainer
82. Steve Miller Band - The Joker
83. Grand Funk - The Loco-Motion
84. Paper Lace - The Night Chicago Died
85. Leo Sayer / Three Dog Night - The Show Must Go On
86. The Sweet - The Sixteens
87. Dionne Warwick & The Spinners - Then Came You
88. Sparks - This Town Ain't Big Enough for Both of Us
89. Mud - Tiger Feet
90. America - Tin Man
91. The Rubettes - Tonight
92. MFSB - TSOP (The Sound of Philadelphia)
93. Mike Oldfield - Tubular Bells
94. Aretha Franklin - Until You Come Back to Me
95. ABBA - Waterloo
96. Three Degrees - When Will I See You Again
97. Bachman–Turner Overdrive - You Ain't Seen Nothing Yet
98. Stevie Wonder - You Haven't Done Nothin'
99. The Stylistics - You Make Me Feel Brand New
100. Barry White - You're the First, The Last, My Everything

Based on the charts of the US and Europe.
The songs are in alphabetical order.
Song snippets are kept short due to copyright reasons.

In this video, we go over how you can fine-tune Llama 3.1 and run it locally on your machine using Ollama! We use the open source repository "Unsloth" to do all of the fine tuning on an SQL dataset!

Throughout this video, we discuss the ins and outs of what fine-tuning an LLM is, how you can work with your data so that the LLM can process it and then importing it into Ollama for you to run locally on your machine!

Ollama is available on all platforms!

Dataset used: https://huggingface.co/dataset....s/gretelai/synthetic
Ollama: https://github.com/ollama/ollama
Unsloth: https://github.com/unslothai/unsloth

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TIMESTAMPS
0:00 Intro
0:10 Getting the dataset
0:45 The Tech Stack
1:18 Installing Dependencies
1:48 Fast Language Model Explained
2:35 LORA Adaptes Explained
3:02 Converting your data to fine-tune
3:36 Training the Model....
4:01 Converting to Ollama compatibility
4:11 Creating a Modelfile for Ollama
4:50 Final Output!
5:01 Check out Ollama in 2 minutes!

For more information about Stanford's online Artificial Intelligence programs visit: https://stanford.io/ai

To learn more about enrolling in this course visit: https://online.stanford.edu/co....urses/cs336-language

To follow along with the course schedule and syllabus visit: https://stanford-cs336.github.io/spring2025/

Percy Liang
Associate Professor of Computer Science
Director of Center for Research on Foundation Models (CRFM)

Tatsunori Hashimoto
Assistant Professor of Computer Science
For more information about Stanford's online Artificial Intelligence programs visit: https://stanford.io/ai

To learn more about enrolling in this course visit: https://online.stanford.edu/co....urses/cs336-language

To follow along with the course schedule and syllabus visit: https://stanford-cs336.github.io/spring2025/

Percy Liang
Associate Professor of Computer Science
Director of Center for Research on Foundation Models (CRFM)

Tatsunori Hashimoto
Assistant Professor of Computer Science

View the entire course playlist: https://www.youtube.com/playli....st?list=PLoROMvodv4r

Deep learning has shown remarkable success in processing and understanding unstructured data like text and images. In this module, we will explore how deep neural networks can be leveraged to build intelligent systems in the domains of natural language processing and computer vision. Get ready to dive into the exciting world of deep learning on text and images!

We will start with the agenda and course overview. Then, we will review some key machine learning concepts, including regression, optimization, regularization, and text and data representation.

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This video is part of Machine Learning University’s open-source "Application of Deep Learning to Text and Image Data" series, part of our Fundamentals of Machine Learning content. Access the full set of lessons, hands-on labs, and Jupyter Notebooks here:

🔗 GitHub Repository: https://github.com/aws-mlu/aws....-mlu-eep-traditional
🔗 Watch More MLU Videos: https://www.youtube.com/@machinelearninguniversity

Machine Learning University provides free, open-source AI/ML educational content for educators. New content is released regularly — subscribe to stay updated.

Non-technical friendly course explaining machine learning and deep learning that everyone can understand.

Full course playlist here: https://www.youtube.com/playli....st?list=PLnrO0TOwDbu

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This Edureka video on "Blockchain Applications" will give you a walkthrough on how traditional applications differ from Blockchain applications and how Blockchain applications are developed. It will also list down the top 5 Blockchain applications that have been developed till date.
Below are the topics covered in this video:
00:00:00 - Introduction
00:00:35 - Traditional application
00:03:00 - Blockchain Applications
00:05:36 - Technology Stack
00:06:45 - Advantage of Dapps
00:08:45 - Top 5 Blockchain Applications

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Prepare for JavaScript interview questions focusing on closures, functions, and currying. Throughout the course, you'll delve into various aspects of JavaScript, such as function declarations, expressions, scopes, and hoisting, as well as learning about advanced concepts like closures and lexical scope. You'll also gain a deeper understanding of currying and its practical applications in JavaScript.

Course created by @RoadsideCoder

Useful Links mentioned in the video -
🎥 var, let and const Video - https://www.youtube.com/watch?v=oUWRxJ19gfE&list=PLKhlp2qtUcSaCVJEt4ogEFs6I41pNnMU5
🎥 map, filter, and reduce Video - https://www.youtube.com/watch?v=dGq0gi0wv64&list=PLKhlp2qtUcSaCVJEt4ogEFs6I41pNnMU5&index=2
🎥 FE Interview Experience Video - https://www.youtube.com/watch?v=vxggZffOqek&list=PLKhlp2qtUcSb_WQZC3sq9Vw3NC4DbreUL&index=1

⭐️ Contents ⭐️
⌨️ (0:00:00) Intro
⌨️ (0:01:48) Function Declaration
⌨️ (0:02:13) Function Expression
⌨️ (0:02:34) Anonymous Function
⌨️ (0:03:25) First Class Functions
⌨️ (0:04:54) What is IIFE?
⌨️ (0:06:05) IIFE - Interview Question
⌨️ (0:06:59) Closures
⌨️ (0:07:27) Function Scopes
⌨️ (0:09:10) Function Scope - Interview Question
⌨️ (0:10:18) Hoisting in Functions
⌨️ (0:13:40) Hoisting - Interview Question
⌨️ (0:15:46) Params vs Arguments
⌨️ (0:16:25) Spread vs Rest Operators
⌨️ (0:17:43) Interview Question on params, args, spread, rest
⌨️ (0:19:03) Callback Function
⌨️ (0:20:02) Callback Function - Interview Questions
⌨️ (0:20:58) Arrow Functions
⌨️ (0:21:59) Arrow function vs Normal Function
⌨️ (0:25:13) Closures
⌨️ (0:25:50) What is Lexical Scope?
⌨️ (0:27:39) Lexical Scope - Interview Question
⌨️ (0:28:53) What is Closure?
⌨️ (0:29:44) Example of Closures
⌨️ (0:30:57) Why Closure?
⌨️ (0:32:20) Closure Scope Chain
⌨️ (0:35:13) Ques 1 - What will it print?
⌨️ (0:37:10) Ques 2 - Write a function for this
⌨️ (0:39:29) Ques 3 - Time Optimisation with Closures
⌨️ (0:42:08) Ques 4 - setTimeout + block scope with Closures
⌨️ (0:47:08) Ques 5 - Create a private counter
⌨️ (0:49:49) Ques 6 - What is Module Pattern?
⌨️ (0:51:40) Ques 7 - Make this run only once
⌨️ (0:54:18) Ques 8 - Once Polyfill Implementation
⌨️ (0:58:11) Ques 9 - Memoise/Caching Implementation
⌨️ (1:03:46) Ques 10 - Closure vs Scope
⌨️ (1:04:25) Currying
⌨️ (1:04:55) What is Curring in Javascript?
⌨️ (1:05:23) Example of Currying
⌨️ (1:08:17) Ques 1 - Implement sum(2)(6)(1)
⌨️ (1:11:02) Ques 2 - Reusing Variable for logic
⌨️ (1:14:09) Ques 3 - Infinite Currying
⌨️ (1:18:27) Ques 4 - Currying vs Partial Application
⌨️ (1:20:37) Ques 5 - Manipulating DOM
⌨️ (1:23:01) Ques 6 - curry() implementation

Provides an intuitive explanation for what deep learning models are doing when they find an 'efficient feature representation'
Full course playlist here: https://www.youtube.com/playli....st?list=PLnrO0TOwDbu