Agentic AI Coding

🔗 Roadmap to become NLP Expert in 2025

🔅 Deep Learning and Generative AI: Data Prep, Analysis, and Visualization with Python 🌐 Author: Gwendolyn Stripling 🔰 Level: Intermediate ⏰ Duration: 1h 56m

🌀 Learn the knowledge and practical skills needed to effectively utilize deep learning techniques using the Python programming language.

📗 Topics: Generative AI, Deep Learning, Python 📤 Join Artificial intelligence for more courses

Machine Learning Algorithms Cheatsheet ✅

🔅 Machine Learning and AI Foundations: Advanced Decision Trees with KNIME 🌐 Author: Keith McCormick 🔰 Level: Advanced ⏰ Duration: 1h 33m

🌀 Learn to go beyond the basic decision tree algorithms in KNIME by accessing WEKA, R, and Python-based decision tree and rule induction algorithms from within the KNIME platform.

📗 Topics: Decision Trees, Knime, Machine Learning 📤 Join Artificial intelligence for more courses

🔅 Trump calls China's DeepSeek AI a "wake-up call"

The sudden rise of a Chinese startup called DeepSeek sent U.S. tech stocks tumbling Monday. DeepSeek says it created an artificial intelligence model in much less time and for much less money than U.S. companies. President Trump called it a "wake-up call."

Generative AI in Data Analytics ✅

🔗 Master AI (Artificial Intelligence) in 10 days 👇👇 Day 1: Introduction to AI - Start with an overview of what AI is and its various applications. - Read articles or watch videos explaining the basics of AI. Day 2-3: Machine Learning Fundamentals - Learn the basics of machine learning, including supervised and unsupervised learning. - Study concepts like data, features, labels, and algorithms. Day 4-5: Deep Learning - Dive into deep learning, understanding neural networks and their architecture. - Learn about popular deep learning frameworks like TensorFlow or PyTorch. Day 6: Natural Language Processing (NLP) - Explore the basics of NLP, including tokenization, sentiment analysis, and named entity recognition. Day 7: Computer Vision - Study computer vision, including image recognition, object detection, and convolutional neural networks. Day 8: AI Ethics and Bias - Explore the ethical considerations in AI and the issue of bias in AI algorithms. Day 9: AI Tools and Resources - Familiarize yourself with AI development tools and platforms. - Learn how to access and use AI datasets and APIs. Day 10: AI Project - Work on a small AI project. For example, build a basic chatbot, create an image classifier, or analyze a dataset using AI techniques.

🛜 Nmap For Penetration Testing: Beginner To Advanced 🌟 4.5 - 416 votes 💰 Original Price: $49.99

📖 Master network mapping, scanning and enumeration with Nmap.

🔊 Taught By: HackerSploit Academy 📤 Download Full Course 📤 Download All Courses

🔅 More Python Tips, Tricks, and Techniques for Data Science 🌐 Author: Harshit Tyagi 🔰 Level: Intermediate ⏰ Duration: 2h 15m

🌀 Deliver valuable insights to your users with Python. Get practical tips and techniques that can help you enhance your Python data science workflow.

📗 Topics: Data Science, Python 📤 Join Data Analysis and Databases for more courses

🔗 Essential Tools, Libraries, and Frameworks to learn Artificial Intelligence 1. Programming Languages: Python R Java Julia 2. AI Frameworks: TensorFlow PyTorch Keras MXNet Caffe 3. Machine Learning Libraries: Scikit-learn: For classical machine learning models. XGBoost: For boosting algorithms. LightGBM: For gradient boosting models. 4. Deep Learning Tools: TensorFlow PyTorch Keras Theano 5. Natural Language Processing (NLP) Tools: NLTK (Natural Language Toolkit) SpaCy Hugging Face Transformers Gensim 6. Computer Vision Libraries: OpenCV DLIB Detectron2 7. Reinforcement Learning Frameworks: Stable-Baselines3 RLlib OpenAI Gym 8. AI Development Platforms: IBM Watson Google AI Platform Microsoft AI 9. Data Visualization Tools: Matplotlib Seaborn Plotly Tableau 10. Robotics Frameworks: ROS (Robot Operating System) MoveIt! 11. Big Data Tools for AI: Apache Spark Hadoop 12. Cloud Platforms for AI Deployment: Google Cloud AI AWS SageMaker Microsoft Azure AI 13. Popular AI APIs and Services: Google Cloud Vision API Microsoft Azure Cognitive Services IBM Watson AI APIs 14. Learning Resources and Communities: Kaggle GitHub AI Projects Papers with Code ENJOY LEARNING 👍👍

🔗 5 Trending AI Jobs You Can’t Miss in 2025! 🤖 💻 Machine Learning Engineer 👉🏻 Average Salary: $114,000 👉🏻 What They Do: Design and implement ML algorithms while collaborating with data scientists and engineers. 📊 📊 Data Scientist 👉🏻 Average Salary: $120,000 👉🏻 What They Do: Analyze data, build predictive models, and drive data-backed decisions. 📈 🔬 AI Research Scientist 👉🏻 Average Salary: $126,000 👉🏻 What They Do: Explore the future of AI by testing algorithms and driving innovation. 🌟 🤝 AI Ethic 👉🏻 Average Salary: $135,000 👉🏻 What They Do: Promote ethical AI development, address biases, and ensure fairness. 🌐 📈 AI Product Manager 👉🏻 Average Salary: $140,000 👉🏻 What They Do: Manage AI products for success, focusing on innovation and ethical impact. 🛠

📖 Dubao 1.5 pro, a new chinese Model. > outperforms on popular benchmarks almost every other LLM > outperforms o1 on AIME > uses MoE with 7 experts > 20b activated parameters China is cooking!