Jackson Koli

Aquarius,...... A fun loving guy,,,Foodie but still thin ...lol..

[Pixelverse @pixelverse_xyz]

$PIXFI will be listed on major centralized exchanges on July 18th at 12 PM.

Stay tuned for more information about the future of $PIXFI and its many token utilities once it goes live.

#PIXELVERSE $PIXFI

[Avicchi @avicchii]

Top 10 horror movies on Netflix 2023

1 The Pope's Exorcist
2 We Have a Ghost
3 The Conference
4 Sister Death
5 Run Rabbit Run
6 Tin & Tina
7 The Strays
8 Bayi Ajaib
9 Asvins
10 Phenomena
11 Reptile
12 Mother's Day
13 Unlocked
14 Bird Box Barcelona
15 Nowhere
16 Fair Play
17 Mother's Day
18 Chokehold
19 Infiesto
20 They Cloned Tyrone

[Inferam @InferamAI]

Why was I never taught this in school?

[Swapna Kumar Panda @swapnakpanda]

Best of the best YouTube Courses for Data Science:

❯ Python
https://t.co/G1w3dCW558

❯ SQL
https://t.co/C0SB4vsvaZ

❯ Data Analyst
https://t.co/S3lJvLEdOR

❯ Data Analysis
https://t.co/GtOvehI700

❯ Excel
https://t.co/1m45P2g6Cp

❯ PowerBI
https://t.co/ZCn7aDYjzL

❯ Tableau
https://t.co/vWLcXmfs9L

❯ Linear Algebra
https://t.co/NiFFV9M9GQ

❯ Calculus
https://t.co/vfHhvjc0VX

❯ Statistics
https://t.co/YSgbsv5zq2

❯ Machine Learning
https://t.co/f4P4Ad0PCU

❯ Deep Learning
https://t.co/4UjJonuUXN

❯ Deep Learning
https://t.co/CAiiRO55Ga

❯ R
https://t.co/FAVMpexL6V

❯ Excel
https://t.co/bWIpIuOiS4

❯ Excel Power Query
https://t.co/ixZYa6mzx7

[Python Coding @clcoding]

Free 365 days Python Coding Challenge https://t.co/4jx7lFxmIA

[Swapna Kumar Panda @swapnakpanda]

Learn Data Science FREE with Certificates:

❯ Python
https://t.co/9OSnj5oOxF

❯ SQL
https://t.co/OyFZOvLGHk

❯ R
https://t.co/xmZAyQc0te

❯ Excel
https://t.co/upRPZO64L4

❯ PowerBI
https://t.co/xupOi567eZ

❯ Tableau
https://t.co/B32g5YsWRM

❯ Mathematics & Statistics
https://t.co/12QdKExHRr

❯ Data Analysis
https://t.co/RNcQyU9kUS

❯ Data Visualization
https://t.co/SmkcXww0GI

❯ Machine Learning
https://t.co/jA8ZFAGhc2

❯ Deep Learning
https://t.co/a8jOtbXmyK

[Every Movie Plug @everymovieplug]

Top 100 military movies of all time.

1. Saving Private Ryan (1998)
2. Apocalypse Now (1979)
3. Full Metal Jacket (1987)
4. Platoon (1986)
5. Black Hawk Down (2001)
6. Das Boot (1981)
7. The Thin Red Line (1998)
8. Paths of Glory (1957)
9. Hacksaw Ridge (2016)
10. 1917 (2019)
11. Dunkirk (2017)
12. Patton (1970)
13. Gallipoli (1981)
14. We Were Soldiers (2002)
15. Bridge on the River Kwai (1957)
16. The Deer Hunter (1978)
17. The Hurt Locker (2008)
18. Letters from Iwo Jima (2006)
19. Zulu (1964)
20. Black Book (2006)
21. Stalingrad (1993)
22. The Battle of Algiers (1966)
23. The Longest Day (1962)
24. The Bridge at Remagen (1969)
25. Zero Dark Thirty (2012)
26. Jarhead (2005)
27. The Patriot (2000)
28. Tora! Tora! Tora! (1970)
29. Master and Commander: The Far Side of the World (2003)
30. Enemy at the Gates (2001)
31. Glory (1989)
32. The Great Escape (1963)
33. All Quiet on the Western Front (1930)
34. The Wind That Shakes the Barley (2006)
35. Lone Survivor (2013)
36. Kelly's Heroes (1970)
37. The Green Berets (1968)
38. The Alamo (1960)
39. The Messenger (2009)
40. 13 Hours: The Secret Soldiers of Benghazi (2016)
41. 12 Strong (2018)
42. The Last of the Mohicans (1992)
43. The Pianist (2002)
44. Rescue Dawn (2006)
45. The Beast of War (1988)
46. A Bridge Too Far (1977)
47. Behind Enemy Lines (2001)
48. Inglourious Basterds (2009)
49. The Boys in Company C (1978)
50. Red Tails (2012)
51. Battle for Haditha (2007)
52. Courage Under Fire (1996)
53. 5 Fingers (1952)
54. Company of Heroes (2013)
55. The Finest Hours (2016)
56. Windtalkers (2002)
57. Battle of the Bulge (1965)
58. The Nightingale (2018)
59. A Midnight Clear (1992)
60. Attack on the Iron Coast (1968)
61. Sergeant York (1941)
62. Empire of the Sun (1987)
63. The Pacific (2010) - Mini-series
64. The Desert Fox: The Story of Rommel (1951)
65. The Pacific (2010) - Mini-series
66. Enemy at the Gates (2001)
67. The Monuments Men (2014)
68. Days of Glory (2006)
69. Fires on the Plain (1959)
70. The Steel Helmet (1951)
71. Battle of the Damned (2013)
72. Memphis Belle (1990)
73. Crimson Tide (1995)
74. Attack on the Iron Coast (1968)
75. Sergeant York (1941)
76. Empire of the Sun (1987)
77. The Pacific (2010) - Mini-series
78. The Desert Fox: The Story of Rommel (1951)
79. Enemy at the Gates (2001)
80. The Monuments Men (2014)
81. Days of Glory (2006)
82. Fires on the Plain (1959)
83. The Steel Helmet (1951)
84. Battle of the Damned (2013)
85. The Longest Day (1962)
86. The Bridge at Remagen (1969)
87. M*A*S*H (1970)
88. Jarhead (2005)
89. The Patriot (2000)
90. Tora! Tora! Tora! (1970)
91. Master and Commander: The Far Side of the World (2003)
92. Glory (1989)
93. The Great Escape (1963)
94. All Quiet on the Western Front (1930)
95. Platoon (1986)
96. Come and See (1985)
97. Hamburger Hill (1987)
98. The Red Badge of Courage (1951)
99. Born on the Fourth of July (1989)
100. Fort Apache (1948)

[Aakash Kanojiya @Kanojiyaaakash1]

Free Certification Courses for Data Science:

🔸Python
https://t.co/y2LHqH9dNb

🔸SQL
https://t.co/bkglzkVZyK

🔸R
https://t.co/qHWid1zLz5

🔸Excel
https://t.co/wAX2huZIqS

🔸PowerBI
https://t.co/V8QY7LS6pE

🔸Tableau
https://t.co/Ak8sRnkyNN

🔸Mathematics & Statistics
https://t.co/hiZumtZc5p

🔸Probability
https://t.co/2JVRcOI7DX

🔸Data Analysis
https://t.co/TL5AxarFGY

🔸Data Visualization
https://t.co/zEud1rK5a7

🔸Data Cleaning
https://t.co/60bD7vdGqq

🔸Machine Learning
https://t.co/1mmRqDud4l

🔸Deep Learning
https://t.co/b2IJE51Zz6

Follow @Kanojiyaaakash1 for such free resources.

[Every Movie Plug @everymovieplug]

Top 100 action movies to watch.

1. Die Hard (1988)
2. Raiders of the Lost Ark (1981)
3. Mad Max: Fury Road (2015)
4. The Dark Knight (2008)
5. Terminator 2: Judgment Day (1991)
6. The Matrix (1999)
7. Gladiator (2000)
8. Inception (2010)
9. Lethal Weapon (1987)
10. Die Hard with a Vengeance (1995)
11. The Bourne Identity (2002)
12. The Avengers (2012)
13. John Wick (2014)
14. The Rock (1996)
15. Speed (1994)
16. Kill Bill: Vol. 1 (2003)
17. Kill Bill: Vol. 2 (2004)
18. The Dark Knight Rises (2012)
19. The Incredibles (2004)
20. The Terminator (1984)
21. Iron Man (2008)
22. The Fifth Element (1997)
23. Gladiator (2000)
24. Braveheart (1995)
25. The Raid: Redemption (2011)
26. The Revenant (2015)
27. Crouching Tiger, Hidden Dragon (2000)
28. 300 (2006)
29. The Avengers: Infinity War (2018)
30. Casino Royale (2006)
31. Predator (1987)
32. Mad Max 2: The Road Warrior (1981)
33. The Equalizer (2014)
34. The Transporter (2002)
35. The Bourne Supremacy (2004)
36. Taken (2008)
37. Edge of Tomorrow (2014)
38. Rambo: First Blood (1982)
39. Aliens (1986)
40. John Wick: Chapter 2 (2017)
41. Gladiator (2000)
42. The Dark Knight Rises (2012)
43. The Hurt Locker (2008)
44. Speed (1994)
45. Captain America: The Winter Soldier (2014)
46. Casino Royale (2006)
47. Kill Bill: Vol. 1 (2003)
48. Kill Bill: Vol. 2 (2004)
49. The Revenant (2015)
50. The Fugitive (1993)
51. 300 (2006)
52. The Matrix Reloaded (2003)
53. The Matrix Revolutions (2003)
54. Avatar (2009)
55. The Wolverine (2013)
56. Casino (1995)
57. RoboCop (1987)
58. The Last of the Mohicans (1992)
59. The Dark Knight (2008)
60. Minority Report (2002)
61. Kingsman: The Secret Service (2014)
62. District 9 (2009)
63. The Rock (1996)
64. X-Men: Days of Future Past (2014)
65. The French Connection (1971)
66. Taken (2008)
67. The Equalizer 2 (2018)
68. Blade Runner (1982)
69. The Patriot (2000)
70. The Hunt for Red October (1990)
71. Casino Royale (2006)
72. Equilibrium (2002)
73. The Book of Eli (2010)
74. Sicario (2015)
75. The Road (2009)
76. Wanted (2008)
77. Leon: The Professional (1994)
78. Face/Off (1997)
79. Mission: Impossible - Fallout (2018)
80. Mad Max: Beyond Thunderdome (1985)
81. The Karate Kid (1984)
82. 28 Days Later (2002)
83. The Italian Job (2003)
84. The Magnificent Seven (1960)
85. Air Force One (1997)
86. Kill Zone (2005)
87. The Grand Budapest Hotel (2014)
88. Total Recall (1990)
89. Indiana Jones and the Last Crusade (1989)
90. Die Hard 2 (1990)
91. Speed (1994)
92. Face/Off (1997)
93. Con Air (1997)
94. 28 Weeks Later (2007)
95. 16 Blocks (2006)
96. Kill Zone 2 (2015)
97. Die Hard: With a Vengeance (1995)
98. Minority Report (2002)
99. The Mechanic (2011)
100. Olympus Has Fallen (2013)

[Sasi 📊📈 @freest_man]

📊Power BI for Data Science Complete Study Plan 📊

Timeline of 6 weeks and you have to dedicate at least 1 hour a day

/🧵/

[Python Developer @PythonDvz]

Learn Python ! Which level are you at as of now ? Let me know in the comments section.
More ☞ https://t.co/qREwGOC47t

#python #programming #developer #morioh #programmer #coding #softwaredeveloper #computerscience #webdev #webdeveloper #webdevelopment #pythonprogramming #ai #ml #artificialintelligence #machinelearning #pythonquiz #datascience

[Jackson Koli @kolijack]

@saidul_dev Yes

[Akshay 🚀 @akshay_pachaar]

Harvard university is offering FREE world class education in Data Science!

Courses cover:
- Python
- Data Visualization
- Probability
- Statistics
- Machine Learning
- Data Science: Capstone

A project-based pedagogy that allows you to learn while building! 🚀

Read more!👇

[Ezekiel @ezekiel_aleke]

Master SQL and Excel with this MEGA thread.

Number 4 is my favorite.

Also comment the resources you need so I can add it to my next thread.

RT.

[First Doctor @FirstDoctor]

Carrot 🥕 is good for eyes.
Lemon 🍋 is good for skin.
Cabbage 🥬 is good for gut.
Banana 🍌 is good for stress.
Pinneaple 🍍is good for cough.
Tomato 🍅 is good for prostate.
Water 🥛is good for your kidney.
Coconut 🥥 is good for diarrhoea.
Avocado 🥑 is good for your heart.
Cucumber 🥒 is good for hydration.
Egg 🥚is good for bones & immunity.
Spinach 🥦 is good for red blood cells.
Watermelon 🍉 is good for erection.
Repost 🔁 is good for others.

[Swapna Kumar Panda @swapnakpanda]

Best YouTube Playlists for Data Science:

❯ Python
https://t.co/G1w3dCW558

❯ SQL
https://t.co/C0SB4vsvaZ

❯ R
https://t.co/FAVMpexL6V

❯ PowerBI
https://t.co/ZCn7aDYjzL

❯ Tableau
https://t.co/vWLcXmfs9L

❯ Excel
https://t.co/1m45P2g6Cp

❯ Data Analysis
https://t.co/GtOvehI700

❯ Data Analyst
https://t.co/S3lJvLEdOR

❯ Linear Algebra
https://t.co/NiFFV9M9GQ

❯ Calculus
https://t.co/vfHhvjc0VX

❯ Statistics
https://t.co/YSgbsv5zq2

❯ Machine Learning
https://t.co/f4P4Ad0PCU

❯ Deep Learning
https://t.co/4UjJonuUXN

❯ Deep Learning
https://t.co/CAiiRO55Ga

❯ Excel Power Query
https://t.co/ixZYa6mzx7

❯ Microsoft Excel
https://t.co/bWIpIuOiS4

[10Alytics @10Alytics]

Becoming a Data Analyst in 3 months

A Road Map For Beginners

(A Thread)

[Shalini Tewari @maybeshalinii]

FULL STACK DEVELOPER Guide🔥

Step 1 → Learn HTML CSS and JS
Step 2 → Learn Git and GitHub
Step 3 → Learn Frontend Frameworks
Step 4 → Learn Nodejs - Python
Step 5 → Learn Database
Step 6 → Build Full Stack Projects
Step 7 → Host Your Project AWS

Step 8→ Apply Jobs🚀

[Santiago @svpino]

To start with Machine Learning:

1. Learn Python
2. Practice using Google Colab

Take these 2 free courses:

• Introduction to Python Programming (Udacity)
• Machine Learning Crash Course (Google)

If you need a bit more time before diving deeper, finish the following Kaggle tutorials:

• Intro to Machine Learning
• Intermediate Machine Learning

At this point, you are ready to finish your first project: The Titanic Challenge on Kaggle.

If Math is not your strong suit, don't worry. I don't recommend you spend too much time learning Math before writing code. Instead, learn the concepts on-demand: Find what you need when needed.

From here, take the Machine Learning specialization in Coursera. It's more advanced, and it will stretch you out a bit.

The top universities worldwide have published their Machine Learning and Deep Learning classes online. Here are some of them:

• MIT 6.S191 Introduction to Deep Learning
• DS-GA 1008 Deep Learning
• UC Berkeley Full Stack Deep Learning
• UC Berkeley CS 182 Deep Learning
• Cornell Tech CS 5787 Applied Machine Learning

Many different books will help you. The attached image will give you an idea of my favorite ones.

Finally, keep these three ideas in mind:

1. Start by working on solved problems so you can find help whenever you get stuck.

2. ChatGPT will help you make progress. Use it to summarize complex concepts and generate questions you can answer to practice.

3. Find a community here on 𝕏 and share your work. Ask questions, and help others.

During this time, you'll deal with a lot. Sometimes, you will feel it's impossible to keep up with everything happening, and you'll be right.

Here are the good news:

Most people understand a tiny fraction of the world of Machine Learning. You don't need more to build a fantastic career in the space.

Focus on finding your path, and Write. More. Code.

That's how you win.