🔹مسیر یادگیری #هوش_مصنوعی و #یادگیری_ماشین
در لیست زیر گام به گام مسیری که باید طی کنید به همراه منابع رایگان یادگیری آمده است
👉Build a Solid Foundation in Mathematics and Statistics
Mathematics for Machine Learning
Statistics for Data Science
👉Learn a Programming Language (Python)
Python for Everybody Specialization
Introduction to Data Analysis with Python
👉Explore AI and ML Tools and Frameworks
The next step in the roadmap to learn AI & ML is to explore AI & ML tools and frameworks Below are the essential tools and frameworks you need to cover
Scikit-learn: Building ML models (classification, regression, clustering).
TensorFlow and Keras: Building deep learning models and neural networks.
PyTorch: Research-focused deep learning framework.
Cloud Platforms: Explore tools like Google Cloud AI, AWS Sagemaker, and Microsoft Azure for ML.
Scikit-learn documentation
Tensorflow basics
Keras basics
PyTorch Guide
Cloud Platforms Roadmap
👉Get Hands-on with Machine Learning Algorithms:
Learn the key algorithms used in Machine Learning and practice implementing them:
Regression: Linear, Ridge, and Logistic regression.
Classification: Decision Trees, Random Forests, SVM, k-Nearest Neighbors.
Clustering: K-Means, Hierarchical, DBSCAN.
Dimensionality Reduction: PCA, t-SNE.
Model Evaluation: Accuracy, precision, recall, F1-score, ROC curves, and confusion matrix.
Here are the learning resources you can follow:
Machine Learning Algorithms: Handbook
Machine Learning Algorithms Guide
👉Dive into Deep Learning & Reinforcement Learning
The next step in the roadmap to learn AI & ML is to master neural networks and reinforcement learning to build advanced AI systems
Deep Learning Specialization
Reinforcement Learning Specialization
👉Explore Natural Language Processing (NLP):
Learn techniques to process, analyze, and generate text using NLP models. Here are the essential topics you need to cover:
Text preprocessing: Tokenization, stemming, lemmatization, stopwords.
Traditional NLP models: Bag of Words, TF-IDF.
Word Embeddings: Word2Vec, GloVe.
Transformer models: BERT, GPT, and their applications in text generation
Hands-On Natural Language Processing with Python
NLP Free Course by Hugging Face
Tensorflow and Keras for NLP
NLP with Sequence Models
👉Learn Image Processing & Computer Vision
The next step in the roadmap to learn AI & ML is to develop expertise in image processing techniques and computer vision
Image Processing Course
Advanced Computer Vision Course
👉Explore Generative AI & LLMs
Work on Real-World Projects
Learn about Generative AI and Large Language Models (LLMs) that are transforming AI research
Generative Adversarial Networks (GANs) Specialization
Generative AI with LLMs
منبع : link
#ML #AI #Artificial_Intelligence
#Machine_Learning #roadmap
معرفی منابع آموزشی مهندسی کامپیوتر 👇👇
📲 @programmers_street
در لیست زیر گام به گام مسیری که باید طی کنید به همراه منابع رایگان یادگیری آمده است
👉Build a Solid Foundation in Mathematics and Statistics
Mathematics for Machine Learning
Statistics for Data Science
👉Learn a Programming Language (Python)
Python for Everybody Specialization
Introduction to Data Analysis with Python
👉Explore AI and ML Tools and Frameworks
The next step in the roadmap to learn AI & ML is to explore AI & ML tools and frameworks Below are the essential tools and frameworks you need to cover
Scikit-learn: Building ML models (classification, regression, clustering).
TensorFlow and Keras: Building deep learning models and neural networks.
PyTorch: Research-focused deep learning framework.
Cloud Platforms: Explore tools like Google Cloud AI, AWS Sagemaker, and Microsoft Azure for ML.
Scikit-learn documentation
Tensorflow basics
Keras basics
PyTorch Guide
Cloud Platforms Roadmap
👉Get Hands-on with Machine Learning Algorithms:
Learn the key algorithms used in Machine Learning and practice implementing them:
Regression: Linear, Ridge, and Logistic regression.
Classification: Decision Trees, Random Forests, SVM, k-Nearest Neighbors.
Clustering: K-Means, Hierarchical, DBSCAN.
Dimensionality Reduction: PCA, t-SNE.
Model Evaluation: Accuracy, precision, recall, F1-score, ROC curves, and confusion matrix.
Here are the learning resources you can follow:
Machine Learning Algorithms: Handbook
Machine Learning Algorithms Guide
👉Dive into Deep Learning & Reinforcement Learning
The next step in the roadmap to learn AI & ML is to master neural networks and reinforcement learning to build advanced AI systems
Deep Learning Specialization
Reinforcement Learning Specialization
👉Explore Natural Language Processing (NLP):
Learn techniques to process, analyze, and generate text using NLP models. Here are the essential topics you need to cover:
Text preprocessing: Tokenization, stemming, lemmatization, stopwords.
Traditional NLP models: Bag of Words, TF-IDF.
Word Embeddings: Word2Vec, GloVe.
Transformer models: BERT, GPT, and their applications in text generation
Hands-On Natural Language Processing with Python
NLP Free Course by Hugging Face
Tensorflow and Keras for NLP
NLP with Sequence Models
👉Learn Image Processing & Computer Vision
The next step in the roadmap to learn AI & ML is to develop expertise in image processing techniques and computer vision
Image Processing Course
Advanced Computer Vision Course
👉Explore Generative AI & LLMs
Work on Real-World Projects
Learn about Generative AI and Large Language Models (LLMs) that are transforming AI research
Generative Adversarial Networks (GANs) Specialization
Generative AI with LLMs
منبع : link
#ML #AI #Artificial_Intelligence
#Machine_Learning #roadmap
معرفی منابع آموزشی مهندسی کامپیوتر 👇👇
📲 @programmers_street
❤3👍2
🧡 دانشجویان علاقمند به فراگیری #هوش_مصنوعی از سراسر ایران و جهان: برای نخستین بار میتوانید به صورت زنده و آنلاین، در کلاس #یادگیری_ماشین دانشکدهی مهندسی کامپیوتر دانشگاه صنعتی شریف شرکت کنید.
🧡 مدرس: دکتر علی شریفی زارچی، عضو هیات علمی گروه هوشمصنوعی و بیوانفورماتیک دانشگاه صنعتی شریف
🧡 تیم تهیهی محتوا: ۷۰ نفر از دانشجویان و دانشآموختگان دانشگاه شریف و سایر دانشگاههای برتر
👑 هزینهی ثبتنام: رایگان
👑 شروع کلاسها: ۱ مهر ۱۴۰۳
👑 اطلاعات بیشتر و ثبتنام: sharifml.ir
#ML #AI #Artificial_Intelligence
#Machine_Learning #roadmap
کانال مهندسی کامپیوتر 👇👇
📲 @programmers_street
🧡 مدرس: دکتر علی شریفی زارچی، عضو هیات علمی گروه هوشمصنوعی و بیوانفورماتیک دانشگاه صنعتی شریف
🧡 تیم تهیهی محتوا: ۷۰ نفر از دانشجویان و دانشآموختگان دانشگاه شریف و سایر دانشگاههای برتر
👑 هزینهی ثبتنام: رایگان
👑 شروع کلاسها: ۱ مهر ۱۴۰۳
👑 اطلاعات بیشتر و ثبتنام: sharifml.ir
#ML #AI #Artificial_Intelligence
#Machine_Learning #roadmap
کانال مهندسی کامپیوتر 👇👇
📲 @programmers_street
👍3❤2
📣 برای دسترسی سادهتر همهی مخاطبان دوره، به خصوص فارسیزبانان خارج از ایران، ویدئوهای دورهی یادگیری ماشین دانشکدهی مهندسی کامپیوتر دانشگاه صنعتی شریف، از این پس از طریق کانال آپارات نیز قابل مشاهده خواهد بود.
#ML #AI #Artificial_Intelligence
#Machine_Learning #roadmap
معرفی منابع آموزشی مهندسی کامپیوتر 👇👇
📲 @programmers_street
#ML #AI #Artificial_Intelligence
#Machine_Learning #roadmap
معرفی منابع آموزشی مهندسی کامپیوتر 👇👇
📲 @programmers_street
❤1
Data Science with Python Courses- https://www.mltut.com/best-data-science-with-python-courses-online/
#MachineLearning #DeepLearning #BigData #Datascience #ML #DataVisualization #ArtificialInteligence #deeplearning #python #AI
دانشکده مهندسی کامپیوتر 👇👇
🆔 @programmers_street
#MachineLearning #DeepLearning #BigData #Datascience #ML #DataVisualization #ArtificialInteligence #deeplearning #python #AI
دانشکده مهندسی کامپیوتر 👇👇
🆔 @programmers_street
👍1