Do you want to learn Machine Learning from scratch? Here we listed Machine Learning tutorials which will help you learn Machine Learning from scratch, and are suitable for beginners, intermediate learners as well as experts.
Machine Learning A-Z™: AI, Python & R + ChatGPT Bonus [2023]
What you’ll learn
- Master Machine Learning on Python & R
- Have a great intuition of many Machine Learning models
- Make accurate predictions
- Make powerful analysis
- Make robust Machine Learning models
- Create strong added value to your business
- Use Machine Learning for personal purpose
- Handle specific topics like Reinforcement Learning, NLP and Deep Learning
- Handle advanced techniques like Dimensionality Reduction
- Know which Machine Learning model to choose for each type of problem
Duration: 46 hours
Rating: 4.5 (167K+ ratings) out of 5
Trainer: 928K+
URL: https://www.udemy.com/course/machinelearning/
A to Z (NLP) Machine Learning Model building and Deployment
What you’ll learn
- Developing the NLP Model for Sentiment analysis and Machine learning deployment on local server using flask and docker.
- Select the most efficient Machine Learning Model,Tune the hyper-parameters and selecting the best model using cross-validation technique
- A quick discussion from the basic in nutshell about DevOps tools like docker, Git and GitLab, Jenkins etc.
- A better understanding about software development and automation in real scenario and concept of end-to-end Integration.
Duration: 3hr 19min Rating: 4.3 (74 ratings) out of 5 Trainer: Mohammed Rijwan Enroll Now:: https://www.udemy.com/course/a-to-z-nlp-machine-learning-model-building-and-deployment/
Mastering Data Science and Machine Learning Fundamentals
What you’ll learn
- Mastering Data Science fundamentals
- Mastering Machine Learning Fundamentals
- How and when to use each Machine Learning model
- Make regression using Linear Regression, SVM, Decsision Trees and Ensemble Modeling
- Classify data using K-Means clustering, Support Vector Machines (SVM), KNN, Decision Trees, Naive Bayes, and PCA
Duration: 3hr 19min Rating: 4.4 (762 ratings) out of 5 Trainer: AI Sciences URL: https://www.udemy.com/course/mastering-data-science-and-machine-learning-fundamentals/
50 Must Know Concepts, Algorithms in Machine Learning
What you’ll learn
- Combined 50 Modules,Techniques,Algorithms of Machine Learning.
- Introduction to must know concepts in Machine Learning which will help you to prepare for interview
- You will get an idea of complete syllabus in Machine Learning
Duration: 54min Rating: 4.0 (115 ratings) out of 5 Trainer: TheMachineLearning.Org URL: https://www.udemy.com/course/must-know-in-machine-learning/
Introduction to Machine Learning for Coders
What you’ll learn
- Introduction to Random Forests
- Random Forest Deep Dive
- Performance, Validation, and Model Interpretation
- Feature Importance. Tree Interpreter
- Extrapolation and RF from Scratch
- Data Products and Live Coding
- RF From Scratch and Gradient Descent
- Gradient Descent and Logistic Regression
- Regularization, Learning Rates, and NLP
- More NLP and Columnar Data
- Embeddings
- Complete Rossmann. Ethical Issues
Duration: around 24 hours Trainer: Fast.ai URL: http://course18.fast.ai/ml
Machine Learning
What you’ll learn
- Supervised learning techniques for regression and classification
- Unsupervised learning techniques for data modeling and analysis
- Probabilistic versus non-probabilistic viewpoints
- Optimization and inference algorithms for model learning
Trainer: John W. Paisley URL: https://www.edx.org/course/machine-learning
Advanced Machine Learning Specialization
What you’ll learn
- Introduction to Deep Learning
- How to Win Data Science Competitions: Learn from Top Kagglers
- Bayesian Methods for Machine Learning
- Practical Reinforcement Learning
- Deep Learning in Computer Vision
- Natural Language Processing
- Addressing the Large Hadron Collider Challenges by Machine Learning
URL: https://www.coursera.org/specializations/aml
Machine Learning
What you’ll learn
- Understand parametric and non-parametric algorithms, clustering, dimensionality reduction, among other important topics.
- Gain best practices and advice from the instructor.
- Interact with your peers in a community of like-minded learners from all levels of experience.
- Real-world based case studies give you the opportunity to understand how problems are solved on a daily basis.
- The flexible deadline allows you to learn at your convenience.
- Learn to apply learning algorithms to build smart robots, understand text, audio, database mining.
Trainer: Andrew Ng Rating: 4.9 (130,294 ratings) URL: https://www.coursera.org/learn/machine-learning
Machine Learning with Python
What you’ll learn
- Regression
- Classification
- Clustering
- Recommender Systems
- Final Project
Trainer: Joseph Santarcangelo, SAEED AGHABOZORGI Rating: 4.7 (6,920 ratings) URL: https://www.coursera.org/learn/machine-learning-with-python
Deep Learning Specialization
What you’ll learn
- Learn about convolutional networks, RNNs, BatchNorm, Dropout and more.
- Different techniques using which you can build models to solve real-life problems.
- Real-world case studies in fields such as healthcare, autonomous driving, sign language reading, music generation, and natural language processing are covered.
Trainer: deeplearning.ai Rating: 4.8 (203,169 ratings) URL: https://www.coursera.org/specializations/deep-learning
Complete Machine Learning & Data Science Bootcamp 2023
What you’ll learn
- Become a Data Scientist and get hired
- Master Machine Learning and use it on the job
- Deep Learning, Transfer Learning and Neural Networks using the latest Tensorflow 2.0
- Use modern tools that big tech companies like Google, Apple, Amazon and Meta use
- Present Data Science projects to management and stakeholders
- Learn which Machine Learning model to choose for each type of problem
- Real life case studies and projects to understand how things are done in the real world
- Learn best practices when it comes to Data Science Workflow
- Implement Machine Learning algorithms
- Learn how to program in Python using the latest Python 3
- How to improve your Machine Learning Models
- Learn to pre process data, clean data, and analyze large data.
- Build a portfolio of work to have on your resume
- Developer Environment setup for Data Science and Machine Learning
- Supervised and Unsupervised Learning
- Machine Learning on Time Series data
- Explore large datasets using data visualization tools like Matplotlib and Seaborn
- Explore large datasets and wrangle data using Pandas
- Learn NumPy and how it is used in Machine Learning
- A portfolio of Data Science and Machine Learning projects to apply for jobs in the industry with all code and notebooks provided
- Learn to use the popular library Scikit-learn in your projects
- Learn about Data Engineering and how tools like Hadoop, Spark and Kafka are used in the industry
- Learn to perform Classification and Regression modelling
- Learn how to apply Transfer Learning
Duration: 44 hrs Rating: 4.6 (15455 ratings) out of 5 Trainer: Andrei Neagoie URL: https://www.udemy.com/course/machinelearning/
Machine Learning Practical: 6 Real-World Applications
What you’ll learn
- How real data science project looks like
- Case Studies in your resume
- How to chain multiple ML algorithms together to achieve the goal
- Most advanced Data Visualization techniques with Seaborn and Matplotlib
- Learn Logistic Regression
- L1 Regularization (Lasso)
- Random Forest Classifier
Duration: 8.5 hrs Rating: 4.4 (2,332 ratings) out of 5 Trainer: Ryan Ahmed, Rony Sulca URL: https://www.udemy.com/course/machine-learning-practical/
Machine Learning with Javascript
What you’ll learn
- Advanced memory profiling to enhance the performance of your algorithms
- Build apps powered by the powerful Tensorflow JS library
- Develop programs that work either in the browser or with Node JS
- Write clean, easy to understand ML code, no one-name variables or confusing functions
- Pick up the basics of Linear Algebra so you can dramatically speed up your code with matrix-based operations. (Don’t worry, I’ll make the math easy!)
- Comprehend how to twist common algorithms to fit your unique use cases
- Plot the results of your analysis using a custom-build graphing library
- Learn performance-enhancing strategies that can be applied to any type of Javascript code
- Data loading techniques, both in the browser and Node JS environments
Duration: 17.5 hrs Rating: 4.6 (2,657 ratings) out of 5 Trainer: Stephen Grider URL: https://www.udemy.com/course/machine-learning-with-javascript/
A Beginner’s Guide To Machine Learning with Unity
What you’ll learn
- genetic algorithms
- neural networks
- human player captured training sets
- reinforcement learning
- Unity’s ML-Agent plugin
- Tensorflow
Duration: 12.5 hrs
Rating: 4.6 (1,711 ratings) out of 5
Trainer: Penny de Byl
URL: https://www.udemy.com/course/machine-learning-with-unity/
