🚓 Deep Learning Roadmap 2024- Step-by-Step Career Path

Are you looking for a step-by-step Deep Learning Roadmap?… If yes, this article is for you. This article will provide a complete Deep Learning Roadmap from scratch. Along with that, you will also find some best resources to learn Deep Learning concepts.

Now without any further ado, let’s get started 👇

🔗 https://www.mltut.com/deep-learning-roadmap/

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☄️ 46 Best Resources to Learn Data Structures and Algorithms including Online Courses, Tutorials, Books, and YouTube Videos 👇

⛓ https://www.mltut.com/best-resources-to-learn-data-structures-and-algorithms/

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🟢 The source of all Python libraries for data science!

🌹 I could not see this complete package of the main Python libraries for data science and not share it with you.

✅ This wonderful GitHub repository covers all Python libraries, packages and tools that are essential for learning and doing data science projects

🔖 Repository access link:

┌ 🏷 Awesome Python Data Science
└ 🗃 GitHub-Repos

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This channels is for Programmers, Coders, Software Engineers.

0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages

✅ https://t.me/addlist/8_rRW2scgfRhOTc0

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♾ 32 essential datasets for data science projects

🔴 The Data Science Dojo website has created a collection of 32 datasets with different levels of difficulty to practice and improve your skills as a data scientist.

✅ This collection includes a diverse range of topics that are classified according to the level of difficulty so that it is suitable for everyone and challenges your theoretical knowledge and practical experience in different parts of data science, such as data cleaning, data visualization, machine learning, etc.


🟢 Basic Level

┌ 🏷 Datasets
├ 🟡 Abalone
├ 🟡 User Knowledge Modeling
├ 🟡 Real Estate Valuation
├ 🟡 Wireless Indoor Localization
├ 🟡Car Evaluation
├ 🟡 Fertility
└ 🟡 Qualitative Bankruptcy


🟡 Intermediate Level

┌ 🏷 Datasets
├ 🔸 Auto MPG
├ 🔸 Heart Disease
├ 🔸 Daily Demand Forecasting Orders
├ 🔸 Blood Transfusion Service Center
├ 🔸 Beijing PM2.5
├ 🔸 Echocardiogram
├ 🔸 Concrete Compressive Strength
├ 🔸 Liver Disorders
├ 🔸Dow Jones Index
├ 🔸Energy Efficiency
├ 🔸 Glass Identification
├ 🔸 Hepatitis
├ 🔸 Wholesale Customers
└ 🔸Travel Reviews
├ 🔸 Istanbul Stock Exchange
├ 🔸 Bike Sharing
├ 🔸 Occupancy Detection
├ 🔸 Census Income
└ 🔸 Coronavirus


🔴 Advanced Level

┌ 🏷 Generative AI for Beginners
├ 🔸 Autism Screening Adult
├ 🔸 Default of Credit Card Clients
├ 🔸 Banknote Authentication
├ 🔸 Individual Household Electric Power
├ 🔸 Online News Popularity
└ 🔸 Amazon Product Reviews

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🙈 8 free NVIDIA artificial intelligence courses

🇸🇾 The NVIDIA site has released a series of artificial intelligence courses that are extremely practical and free for students who want to learn more about this field and are still at the beginning of the journey. 💯


1️⃣ Generative AI Explained course
📝 Definition of productive intelligence and how it works
🗂 Link: LINK


2️⃣ Building A Brain course
📝 How neural networks use data for learning.
🗂 Link: LINK


3️⃣ Augment your LLM Using RAG course
📝 Familiarity with RAG recovery process.
🗂 Link: LINK


4️⃣ Intro to AI in the Data Center course
📝 What is artificial intelligence and its applications.
🗂 Link: LINK


5️⃣ Accelerate Data Science Workflows course
📝 Understand the benefits of integrated workflow between CPUs and GPUs for data science tasks.
🗂 Link: LINK


6️⃣ Recommender Systems course
📝 Strategies used to excel in a data science competition focused on building a recommendation system.
🗂 Link: LINK


7️⃣ Introduction to Networking course
📝 What is the network and why it is needed.
🗂 Link: LINK


8️⃣ Large-Scale Image Classification course
An introduction to large-scale image classification.
🗂 Link: LINK

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📚 10 of the best free books in the field of data science
📑 that you should include in your learning program!

1️⃣ Python Data Science Handbook
📝 Using unique Python libraries with a focus on data science.
📕 Link: PDF


2️⃣ Hands-On Machine Learning book
📝 This book explains the concepts of machine learning with practical examples and Python code and is suitable for novice programmers.
📕 Link: PDF


3️⃣ Deep Learning book
📝 The best book for machine learning and deep learning written by 3 active and top researchers in these fields.
📕 Link: PDF


4️⃣ R for Data Science book
📝 This book reflects the best ways to use R in data science.
📕 Link: PDF


5️⃣ Data Science from Scratch book
📝 This book starts from the simplest possible level and provides you with all the necessary tools and skills to become a great data scientist.
📕 Link: PDF


6️⃣ Machine Learning Yearning book
📝 Error detection in machine learning projects.
📕 Link: PDF


7️⃣ Bayesian Methods for Hackers book
📝 Practical applications of Bayesian inference and probabilistic programming.
📕 Link: PDF


8️⃣ The Elements of Statistical Learning book
📝 Investigating the mathematics of ML algorithms and statistical learning methods.
📕 Link: PDF


9️⃣ DATA SMART book
📝 Implementing complex data science problems using Excel and the tips and tricks of this process.
📕 Link: PDF


🔟 Intro to Statistical Learning with Python book
📝 Examples and practical applications of Python language in data science projects.
📕 Link: PDF

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✅ +70 machine learning projects with Python with data set

🔴 With a simple search on the Internet, you can understand that many datasets are available for use in machine learning projects. I tried to collect more than 70 machine learning projects with Python along with datasets for machine learning beginners and experts with real world implementation.

🔻 You can access all these projects through the following link: 👇

┌ 🏷 70+ ML Datasets & Project Ideas
└ 📚 ML Projects + Datasets


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🟢 5 free courses of productive artificial intelligence
📣 Comprehensive introduction to Generative AI and LLM
🔄 2024 update

⭐️ Google has updated its free artificial intelligence course, and now this course includes 5 sections , and it is extremely useful for students who want to learn more about the field of artificial intelligence and are still in the beginning. 💯

To access these free courses, you can use the following link:


┌ 🏷 Introduction to GenAI
└ 🌐 Website

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🔥 Large selection of interview questions on DS, AI, ML, DL, NLP, computer vision.

A selection of interview questions will help you in interviews in the fields of data science, artificial intelligence, machine learning, deep learning, natural language processing, computer vision.

🟢 100 machine learning interview questions in 2024

🟢 50 computer vision interview questions in 2024

🟢 50 Deep Learning Interview Questions in 2024

🟢 50 interview questions on NLP (natural language processing) in 2024

🟢 100 Data Science interview questions

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🖥 Fake news Detection Machine Learning Project with 92%Accuracy

✅ it contain compressed file in which "jupyter notebook file and dataset" ✅

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🤖 dear data scientists; You don't need to write code in Jupyter notebook anymore! With the Anaconda Assistant added to Jupiter Notebook, you can write a prompt and the code you want will be generated automatically!

Anaconda Assistant brings productive artificial intelligence to Python and data analysis and makes working with data easy for anyone. You can access this feature for free in your Anaconda notebook! 💯

💬 Among the uses of Anaconda Assistant:

🚀 Generate code and improve the coding experience
📊 Data visualization and analysis with more efficiency
📈 drawing diagrams
🐱 Explanation of the data frame and comments

🔖 Anaconda Assistant training guide:

┌ 🏷 Anaconda Assistant
├ 🚀 Anaconda Assistant
└ 🔖 Getting started

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🖥 The most comprehensive educational resource for learning NLP

✅ If you want to have the most comprehensive educational resource for learning NLP , The Index NLP Don't miss it in any way! This site is recommended as a comprehensive and vital resource for people interested in NLP research, which includes more than 9000 related articles and codes , helping you to easily find the codes and articles you need to understand and implement your new research. .

This wonderful resource was launched by Quantum Stat and includes information such as article titles, abstracts, authors, and links to related articles and code repositories. You also have the possibility of quick search and connection diagrams between similar articles


┌ 🏷 The NLP Index
└ 💣 The NLP Index

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🦾 Made With ML : Learn how to combine machine learning with software engineering to design, develop, deploy and iterate on production-grade ML applications.

A 100% free course that will help you learn how to write production-grade MLOps code.

The course will teach you everything from design, modeling, testing, working with learning models and much more for free!

More than 35 thousand stars on Github

Learn how to design, develop, deploy, and operate production-grade ML applications.

▪ Course
▪ Overview
▪ Jupyter notebook

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☄️ Top 12 YouTube Channels to Learn Python

💐 Python will include 57% of data scientist job ads in 2024 . It is still the number one programming language for data scientists.

✅ Now, if you are looking for the best resources to improve your Python skills, after searching and reviewing various resources, I have prepared a list of 12 top channels that provide first-class Python training, which can turn beginners into professional Python programmers. convert


🎬 Python Programmer channel
┤ 📈 211 videos / 465K SUB
┘ 🔴 Link: Python Programmer


🎬 Luke Barousse channel
┤ 📈 157 videos / 429K SUB
┘ 🔴 Link: Luke Barousse


🎬 codebasics channel
┤ 📈 837 videos / 990K SUB
┘ 🔴 link: codebasics


🎬 StatQuest channel with Josh Starmer
┤ 📈 271 videos / 1.14M SUB
┘ 🔴 Link: StatQuest with Josh Starmer


🎬 Sundas Khalid channel
┤ 📈 143 videos / 203K SUB
┘ 🔴 Link: Sundas Khalid


🎬 Shashank Kalanithi channel
┤ 📈 152 videos / 148K SUB
┘ 🔴 Link: Shashank Kalanithi


🎬 Programming with Mosh channel
┤ 📈 203 videos / 3.85M SUB
┘ 🔴 Link: Programming with Mosh


🎬 Corey Schafer channel
┤ 📈 233 videos / 129K SUB
┘ 🔴 Link: Corey Schafer


🎬 sentdex channel
┤ 📈 1254 videos / 1.3M SUB
┘ 🔴 link: sentdex


🎬 Patrick Loeber channel
┤ 📈 206 videos / 264K SUB
┘ 🔴 Link: Patrick Loeber


🎬 Socratica channel
┤ 📈 659 videos / 876K SUB
┘ 🔴 Link: Socratica


🎬 Tech With Tim channel
┤ 📈 983 videos / 1.48M SUB
┘ 🔴 Link: Tech With Tim

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🔥 Large selection of interview questions on DS, AI, ML, DL, NLP, computer vision.

✅ Machine learning interview questions and answers for data scientists

✅ Deep Learning Interview Questions and Answers for Data Scientists

✅ Statistics questions

✅ Questions on probability theory

✅ Repository for a line of online courses on statistics

✅ Questions and answers for data scientists in Python

✅ SQL and DB Interview Questions and Answers for Data Scientists
Questions Based on Resumes

✅ Large Language Model (LLM) Interview Questions and Answers

✅ Questions and answers to interviews on computer vision part 1

✅ Computer vision interview questions and answers part 2

✅ Questions and answers to computer vision interviews part 3

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✅ Learn PyTorch in 4 steps

👨🏻‍💻 With support for more than 200 different mathematical operations, PyTorch is one of the most powerful open source and computational libraries based on Python for machine learning. You don't need to look for different sources to learn this popular library, but the website of this library covers more than what you need.💯

2️⃣ Here, I will teach you how to learn PyTorch from scratch in 4 steps. 👌🏼


1️⃣ Text tutorial: If you don't know anything about Python, you should start learning from here.
⬅️ Topics: tensors, datasets and DataLoader, model building, optimization loop, saving, loading and using the model.

📄 PyTorch Basics
┘📎 Link: Learn the Basics


2️⃣ Video training: This section is very useful for those who prefer video content.
⬅️ Topics: introduction, tensor construction and model construction with pytorch.

📄 Introduction to PyTorch
┘📎 Link: Introduction to PyTorch


3️⃣ Examining examples: By viewing different examples, you will review what you have learned so far.

📄 Learning Python by example
┘📎 Link: Learning PyTorch with Examples


4️⃣ Coding: This step is vital! Your theoretical knowledge is worthless without coding! The Keras website is full of sample code that is great for getting started.

📄 Start coding
┘📎 Link: keras.io

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