Video yükleniyor...

Video Yüklenemedi

Bu video yüklenirken bir sorun oluştu. Bu geçici bir ağ sorunundan kaynaklanıyor olabilir veya video kullanılamıyor olabilir.

Ana Sayfaya Dön

Project: #FakeNews Detector Using #Python and #ML. Models: DecisionTree Classifiers. Logistic Regression Model. Random Forest Classification ID: FE/23/68871350 #3MTTLearningCommunity #My3MTT 3MTT Nigeria Github Repo to project:

Yusuf Nasir Ahmad

1,408 subscribers

13,193 görüntüleme • 2 yıl önce •via X (Twitter)

Haberler & Politika #FakeNews #Python #ML #3MTTLearningCommunity #My3MTT

Anya Rossi• Live Now

Private livecam show

10 Yorum

Shamsuddeen Jibril Bagaldi profil fotoğrafı

Shamsuddeen Jibril Bagaldi2 yıl önce

@3MTTNigeria I wish you all the best sir

Yusuf Nasir Ahmad profil fotoğrafı

Yusuf Nasir Ahmad2 yıl önce

@3MTTNigeria Thank you so much Drone Master

Th3Cl0udGuy ☁️💚🌙 profil fotoğrafı

Th3Cl0udGuy ☁️💚🌙2 yıl önce

@3MTTNigeria May Almighty Allah put Barakah in it brother (ameen)

Yusuf Nasir Ahmad profil fotoğrafı

Yusuf Nasir Ahmad2 yıl önce

@3MTTNigeria Cyber Security, check the work on Github and check how Fake News breed security threats in Nigeria. I am open for Colab sir.

Yusuf Hamisu profil fotoğrafı

Yusuf Hamisu2 yıl önce

@3MTTNigeria Best wishes, Nasiru

Yusuf Nasir Ahmad profil fotoğrafı

Yusuf Nasir Ahmad2 yıl önce

@3MTTNigeria Thanks so much Mr. Opportunity. Kindly have time to review the Project on Github.

Abdullahi Salihu profil fotoğrafı

Abdullahi Salihu2 yıl önce

@3MTTNigeria Nice one Nasir, keep it up

Yusuf Nasir Ahmad profil fotoğrafı

Yusuf Nasir Ahmad2 yıl önce

@3MTTNigeria Dr. I hope you will get to patronize the project and build on it. It is available on Github.

GieDee profil fotoğrafı

GieDee2 yıl önce

@3MTTNigeria More power to your elbow Champ!

Yusuf Nasir Ahmad profil fotoğrafı

Yusuf Nasir Ahmad2 yıl önce

@3MTTNigeria Thanks Boss

Benzer Videolar

My name is Abubakar Muhammad Cohort 2 Member of 3MTT Program fellow ID: FE/23/66409658 Location: Kaduna State. Course: Cybersecurity My knowledge showcase. #My3MTT #3MTTLearningCommunity #3MTT

My name is Abubakar Muhammad Cohort 2 Member of 3MTT Program fellow ID: FE/23/66409658 Location: Kaduna State. Course: Cybersecurity My knowledge showcase. #My3MTT #3MTTLearningCommunity #3MTT

Sadiq 🇳🇬🇵🇸

34,715 görüntüleme • 1 yıl önce

a playlist of 30 youtube videos to learn machine learning fundamentals from scratch if you're struggling on where to start learning ML, this list goes this "Machine Learning: Teach by Doing" is a solid choice to learn both theory and code. (1) Introduction to Machine Learning Teach by Doing: (2) What is Machine Learning? History of Machine Learning: (3) Types of ML Models: (4) 6 steps of any ML project: (5) Install Python and VSCode and run your first code: (6) Linear Classifiers Part 1: (7) Linear Classifiers Part 2: (8) Jupyter Notebook, Numpy and Scikit-Learn: (9) Running the Random Linear Classifier Algorithm in Python: (10) The oldest ML model - Perceptron: (11) Coding the Perceptron: (12) Perceptron Convergence Theorem: (13) Magic of features in Machine Learning: (14) One hot encoding: (15) Logistic Regression Part 1: (16) Cross Entropy Loss: (17) How gradient descent works: (18) Logistic Regression from scratch in Python: (19) Introduction to Regularization: (20) Implementing Regularization in Python: (21) Linear Regression Introduction: (22) Ordinary Least Squares step by step implementation: (23) Ridge regression fundamentals and intuition: (24) Regression recap for interviews: (25) Neural network architecture in 30 minutes: (26) Backpropagation intuition: (27) Neural network activation functions: (28) Momentum in gradient descent: (29) Hands on neural network training in Python: (30) Introduction to Convolutional Neural Networks (CNNs):

a playlist of 30 youtube videos to learn machine learning fundamentals from scratch if you're struggling on where to start learning ML, this list goes this "Machine Learning: Teach by Doing" is a solid choice to learn both theory and code. (1) Introduction to Machine Learning Teach by Doing: (2) What is Machine Learning? History of Machine Learning: (3) Types of ML Models: (4) 6 steps of any ML project: (5) Install Python and VSCode and run your first code: (6) Linear Classifiers Part 1: (7) Linear Classifiers Part 2: (8) Jupyter Notebook, Numpy and Scikit-Learn: (9) Running the Random Linear Classifier Algorithm in Python: (10) The oldest ML model - Perceptron: (11) Coding the Perceptron: (12) Perceptron Convergence Theorem: (13) Magic of features in Machine Learning: (14) One hot encoding: (15) Logistic Regression Part 1: (16) Cross Entropy Loss: (17) How gradient descent works: (18) Logistic Regression from scratch in Python: (19) Introduction to Regularization: (20) Implementing Regularization in Python: (21) Linear Regression Introduction: (22) Ordinary Least Squares step by step implementation: (23) Ridge regression fundamentals and intuition: (24) Regression recap for interviews: (25) Neural network architecture in 30 minutes: (26) Backpropagation intuition: (27) Neural network activation functions: (28) Momentum in gradient descent: (29) Hands on neural network training in Python: (30) Introduction to Convolutional Neural Networks (CNNs):

ℏεsam

117,570 görüntüleme • 1 yıl önce

if you're struggling on where to start learning ML, here’s a playlist of 30 youtube videos to learn machine learning fundamentals from scratch "Machine Learning: Teach by Doing" is a solid choice to learn both theory and code. (1) Introduction to Machine Learning Teach by Doing: (2) What is Machine Learning? History of Machine Learning: (3) Types of ML Models: (4) 6 steps of any ML project: (5) Install Python and VSCode and run your first code: (6) Linear Classifiers Part 1: (7) Linear Classifiers Part 2: (8) Jupyter Notebook, Numpy and Scikit-Learn: (9) Running the Random Linear Classifier Algorithm in Python: (10) The oldest ML model - Perceptron: (11) Coding the Perceptron: (12) Perceptron Convergence Theorem: (13) Magic of features in Machine Learning: (14) One hot encoding: (15) Logistic Regression Part 1: (16) Cross Entropy Loss: (17) How gradient descent works: (18) Logistic Regression from scratch in Python: (19) Introduction to Regularization: (20) Implementing Regularization in Python: (21) Linear Regression Introduction: (22) Ordinary Least Squares step by step implementation: (23) Ridge regression fundamentals and intuition: (24) Regression recap for interviews: (25) Neural network architecture in 30 minutes: (26) Backpropagation intuition: (27) Neural network activation functions: (28) Momentum in gradient descent: (29) Hands on neural network training in Python: (30) Introduction to Convolutional Neural Networks (CNNs):

if you're struggling on where to start learning ML, here’s a playlist of 30 youtube videos to learn machine learning fundamentals from scratch "Machine Learning: Teach by Doing" is a solid choice to learn both theory and code. (1) Introduction to Machine Learning Teach by Doing: (2) What is Machine Learning? History of Machine Learning: (3) Types of ML Models: (4) 6 steps of any ML project: (5) Install Python and VSCode and run your first code: (6) Linear Classifiers Part 1: (7) Linear Classifiers Part 2: (8) Jupyter Notebook, Numpy and Scikit-Learn: (9) Running the Random Linear Classifier Algorithm in Python: (10) The oldest ML model - Perceptron: (11) Coding the Perceptron: (12) Perceptron Convergence Theorem: (13) Magic of features in Machine Learning: (14) One hot encoding: (15) Logistic Regression Part 1: (16) Cross Entropy Loss: (17) How gradient descent works: (18) Logistic Regression from scratch in Python: (19) Introduction to Regularization: (20) Implementing Regularization in Python: (21) Linear Regression Introduction: (22) Ordinary Least Squares step by step implementation: (23) Ridge regression fundamentals and intuition: (24) Regression recap for interviews: (25) Neural network architecture in 30 minutes: (26) Backpropagation intuition: (27) Neural network activation functions: (28) Momentum in gradient descent: (29) Hands on neural network training in Python: (30) Introduction to Convolutional Neural Networks (CNNs):

ℏεsam

108,861 görüntüleme • 1 yıl önce

~~America’s~~ GitHub’s Next Top Model (Update): You can now integrate GitHub Models directly into your repo to compare model options for your next AI project.

America’s GitHub’s Next Top Model (Update): You can now integrate GitHub Models directly into your repo to compare model options for your next AI project.

Thomas Dohmke

11,545 görüntüleme • 1 yıl önce

I've open sourced this project! - use voice commands to change interaction mode (drag, rotate, scale, animate) - use hand gestures to control the 3D model - drag/drop to import other models (only GLTF format supported rn) created using Three.js, Rosebud AI, mediapipe computer vision, web speech API, and Quaternius 3D models 🔗 github repo below

I've open sourced this project! - use voice commands to change interaction mode (drag, rotate, scale, animate) - use hand gestures to control the 3D model - drag/drop to import other models (only GLTF format supported rn) created using Three.js, Rosebud AI, mediapipe computer vision, web speech API, and Quaternius 3D models 🔗 github repo below

AA

40,230 görüntüleme • 1 yıl önce

Name: Yusuf Hawau Yetunde Fellow ID: FE/23/91608191 I started my 3mtt journey few months ago and look at me today, sharing my experience with all what I’ve learnt so far, I trust the process and I’m so proud of my Growth and Progress. Thank you 3MTT Nigeria

Name: Yusuf Hawau Yetunde Fellow ID: FE/23/91608191 I started my 3mtt journey few months ago and look at me today, sharing my experience with all what I’ve learnt so far, I trust the process and I’m so proud of my Growth and Progress. Thank you 3MTT Nigeria

Nana Hawau💜🌸

19,148 görüntüleme • 2 yıl önce

I'm excited to introduce my AI Machine Learning Agent that built 32 ML models in 30 seconds. Today, I'll share with you how to automate building 100s of ML models with the AI ML Agent, which is available on GitHub. We'll create an ML Agent focusing on a Customer Churn Problem. I'll guide you through setting up the ML Agent, creating dozens of ML models, and loading the best model for production. This AI is a huge time-saver! Table of Contents: 00:00 Introduction to my AI Data Science Team 02:56 Setting Up AI Data Science Team 04:48 Running the ML Agent Code 07:12 Create (and Run) the AI Machine Learning Agent 09:53 Reviewing ML Model Summary 12:00 Saving and Loading Models 13:00 Next Steps + Project Roadmap + AI Bootcamp Github to AI Data Science Team (Data Science Agents): Get the Code and Future Updates by Joining my Python AI/ML Tips Newsletter: P.S. - Want to learn how to build AI projects companies actually want? (live Python Code) On Wednesday, May 21st, I'm sharing one of my best AI Projects: AI Customer Segmentation Agent with Python Register here (570+ registered):

I'm excited to introduce my AI Machine Learning Agent that built 32 ML models in 30 seconds. Today, I'll share with you how to automate building 100s of ML models with the AI ML Agent, which is available on GitHub. We'll create an ML Agent focusing on a Customer Churn Problem. I'll guide you through setting up the ML Agent, creating dozens of ML models, and loading the best model for production. This AI is a huge time-saver! Table of Contents: 00:00 Introduction to my AI Data Science Team 02:56 Setting Up AI Data Science Team 04:48 Running the ML Agent Code 07:12 Create (and Run) the AI Machine Learning Agent 09:53 Reviewing ML Model Summary 12:00 Saving and Loading Models 13:00 Next Steps + Project Roadmap + AI Bootcamp Github to AI Data Science Team (Data Science Agents): Get the Code and Future Updates by Joining my Python AI/ML Tips Newsletter: P.S. - Want to learn how to build AI projects companies actually want? (live Python Code) On Wednesday, May 21st, I'm sharing one of my best AI Projects: AI Customer Segmentation Agent with Python Register here (570+ registered):

Matt Dancho (Business Science)

35,428 görüntüleme • 1 yıl önce

I'm excited to introduce my AI Machine Learning Agent that built 32 ML models in 30 seconds. Today, I'll share with you how to automate building 100s of ML models with the AI ML Agent, which is available on GitHub. We'll create an ML Agent focusing on a Customer Churn Problem. I'll guide you through setting up the ML Agent, creating dozens of ML models, and loading the best model for production. This AI is a huge time-saver! Table of Contents: 00:00 Introduction to my AI Data Science Team 02:56 Setting Up AI Data Science Team 04:48 Running the ML Agent Code 07:12 Create (and Run) the AI Machine Learning Agent 09:53 Reviewing ML Model Summary 12:00 Saving and Loading Models 13:00 Next Steps + Project Roadmap + AI Bootcamp Github to AI Data Science Team (Army of Copilots): Get the Code and Future Updates by Joining my Python AI/ML Tips Newsletter: P.S. - Want to learn how to build AI projects companies actually want? (live Python Code) On Wednesday, January 29th, I'm sharing one of my best AI Projects: Time Series Forecasting with AI Register here (1570+ registered):

I'm excited to introduce my AI Machine Learning Agent that built 32 ML models in 30 seconds. Today, I'll share with you how to automate building 100s of ML models with the AI ML Agent, which is available on GitHub. We'll create an ML Agent focusing on a Customer Churn Problem. I'll guide you through setting up the ML Agent, creating dozens of ML models, and loading the best model for production. This AI is a huge time-saver! Table of Contents: 00:00 Introduction to my AI Data Science Team 02:56 Setting Up AI Data Science Team 04:48 Running the ML Agent Code 07:12 Create (and Run) the AI Machine Learning Agent 09:53 Reviewing ML Model Summary 12:00 Saving and Loading Models 13:00 Next Steps + Project Roadmap + AI Bootcamp Github to AI Data Science Team (Army of Copilots): Get the Code and Future Updates by Joining my Python AI/ML Tips Newsletter: P.S. - Want to learn how to build AI projects companies actually want? (live Python Code) On Wednesday, January 29th, I'm sharing one of my best AI Projects: Time Series Forecasting with AI Register here (1570+ registered):

🔥 Matt Dancho (Business Science) 🔥

240,806 görüntüleme • 1 yıl önce

🚀 Ready to build an LLM-powered project? In this video course, Dr. Jodie Burchell will guide you through building a book recommender using cutting-edge NLP techniques, from vector search to zero-shot classification, all using Python. Watch it now:

🚀 Ready to build an LLM-powered project? In this video course, Dr. Jodie Burchell will guide you through building a book recommender using cutting-edge NLP techniques, from vector search to zero-shot classification, all using Python. Watch it now:

PyCharm, a JetBrains IDE

19,374 görüntüleme • 1 yıl önce

To generate 3D models in Codex with text-to-cad: Start a new project, write your prompt for a 3D model, and include a link to clone the text-to-cad repo. Codex handles the rest. The repo is open source and all scripts / ui run locally. Link below.

To generate 3D models in Codex with text-to-cad: Start a new project, write your prompt for a 3D model, and include a link to clone the text-to-cad repo. Codex handles the rest. The repo is open source and all scripts / ui run locally. Link below.

Jake Fitzgerald

22,113 görüntüleme • 1 ay önce

You can now import any GitHub repo into v0 and work on your actual codebase. View your project, edit it, and ship changes to production. All without leaving v0.

You can now import any GitHub repo into v0 and work on your actual codebase. View your project, edit it, and ship changes to production. All without leaving v0.

v0

73,570 görüntüleme • 4 ay önce

Jarvis is now reality. My GPT-4 coding assistant can now build & deploy brand new web apps! It initializes my project, builds my app, creates a GitHub repo, and deploys it to Vercel. All from simply using my voice.

Mckay Wrigley

2,197,267 görüntüleme • 3 yıl önce

New project idea but left the laptop at home? 😬 Create a repo right from your phone. Name it, set visibility, and adjust the details in the GitHub Mobile app. 📱

New project idea but left the laptop at home? 😬 Create a repo right from your phone. Name it, set visibility, and adjust the details in the GitHub Mobile app. 📱

GitHub

52,488 görüntüleme • 14 gün önce

Project DeepWiki Up-to-date documentation you can talk to, for every repo in the world. Think Deep Research for GitHub – powered by Devin. It’s free for open-source, no sign-up! Visit deepwiki com or just swap github → deepwiki on any repo URL:

Project DeepWiki Up-to-date documentation you can talk to, for every repo in the world. Think Deep Research for GitHub – powered by Devin. It’s free for open-source, no sign-up! Visit deepwiki com or just swap github → deepwiki on any repo URL:

Cognition

981,090 görüntüleme • 1 yıl önce

I made an AI data science team with Python. I'm excited to share my new project, the AI Data Science Team, a Python package for creating AI co-pilots and agents to assist in common data science tasks. I walk you through the GitHub page, showcasing the progress and potential of this project. I'll explain how these agents can streamline tasks like code generation and modeling pipeline creation, making data science projects more efficient. Introduction to AI Data Science Team Project Integrating Human-in-the-Loop Example: Accessing Agents for Feature Engineering Setting up Feature Engineering Agent Code On GitHub: Python AI-Tips Newsletter (stay updated as I build this project in the open):

I made an AI data science team with Python. I'm excited to share my new project, the AI Data Science Team, a Python package for creating AI co-pilots and agents to assist in common data science tasks. I walk you through the GitHub page, showcasing the progress and potential of this project. I'll explain how these agents can streamline tasks like code generation and modeling pipeline creation, making data science projects more efficient. Introduction to AI Data Science Team Project Integrating Human-in-the-Loop Example: Accessing Agents for Feature Engineering Setting up Feature Engineering Agent Code On GitHub: Python AI-Tips Newsletter (stay updated as I build this project in the open):

Matt Dancho (Business Science)

11,799 görüntüleme • 1 yıl önce

Easily add skills from repos to your local project. 🛠️ Simply choose your config, pick your skills from the repo, and start using them immediately.

Easily add skills from repos to your local project. 🛠️ Simply choose your config, pick your skills from the repo, and start using them immediately.

Google Antigravity

107,729 görüntüleme • 4 ay önce

Turn any GitHub repository into LLM-ready text! Simply replace "hub" with "ingest" in a GitHub URL and receive a prompt-friendly text ingest for LLMs. Gitingest is 100% open-source and provides: - Directory structure - A brief summary of the project - The entire content as LLM-ready text Plus, it comes with a nice python package and you can run the UI locally! Stay tuned, I'm working on something really cool with this!✨ Link to the GitHub repo in the next tweet! _____ Find me → Akshay 🚀 ✔️ For more insights and tutorials on ML and AI Engineering!

Turn any GitHub repository into LLM-ready text! Simply replace "hub" with "ingest" in a GitHub URL and receive a prompt-friendly text ingest for LLMs. Gitingest is 100% open-source and provides: - Directory structure - A brief summary of the project - The entire content as LLM-ready text Plus, it comes with a nice python package and you can run the UI locally! Stay tuned, I'm working on something really cool with this!✨ Link to the GitHub repo in the next tweet! _____ Find me → Akshay 🚀 ✔️ For more insights and tutorials on ML and AI Engineering!

Akshay 🚀

191,226 görüntüleme • 1 yıl önce

Excited to share the release of VideoPrism! 🎥 📏Generate video embeddings 👀Useful for classifiers, video retrieval, and localization 🔧Adaptable for your tasks Model: Paper: GitHub:

Excited to share the release of VideoPrism! 🎥 📏Generate video embeddings 👀Useful for classifiers, video retrieval, and localization 🔧Adaptable for your tasks Model: Paper: GitHub:

Omar Sanseviero

38,169 görüntüleme • 11 ay önce

Friendly reminder that you can go to any GitHub repo, press the . key, and the entire repo will open in the browser using Visual Studio Code

Friendly reminder that you can go to any GitHub repo, press the . key, and the entire repo will open in the browser using Visual Studio Code

Visual Studio Code

209,336 görüntüleme • 1 yıl önce