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**Best Udemy courses for Machine Learning**:-

**Want to learn Machine Learning, but confused about where to start from? well here are some Udemy courses to help clear your confusion.**

Machine Learning is the process of teaching a machine from past experiences and the data provided without being explicitly programmed with minimal human interaction. It is a sub- branch of Artificial Intelligence (AI). Machine Learning is continuously evolving and has gained very fresh momentum with the innovation in technologies. We are here with some excellent options to learn machine learning and its implementation with real time projects.

**1. Machine Learning A- Z™: Hands-On Python & R In Data Science**

Interested in the field of machine learning and programming in Python and R? Well, then this Udemy course is for you. It will help you walk step by step into the profession of machine learning with an understanding of Data Science as a subdomain and its uses to successfully develop and deploy machine learning models.

**What You will learn:**

- Master Machine Learning with Python and R programming
- Have a great intuition of different Machine Learning models
- Making accurate predictions
- Making powerful analysis
- Making robust Machine Learning models
- Using Machine Learning for personal purpose
- Handling specific topics like Reinforcement Learning, NLP (Natural Language Processor) and Deep Learning
- Handling advanced techniques like Dimensional Reduction
- Know which Machine Learning model to choose for a different type of problem
- Building powerful Machine Learning models and how to combine them to solve any problem

**2. Machine Learning, Data Science and Deep Learning with Python**

Machine Learning and Artificial Intelligence are everywhere nowadays. This Udemy course will provide you with all the insights into different topics of machine learning, data science, and deep learning. You will need some prior coding or scripting experience with at least high school level math skills to carry forward this course and learn different tricks and tactics of machine learning and artificial intelligence.

**What You will learn:**

- Building an artificial neural networks with the help of Tensorflow and Keras
- Classifying images, data, and sentiments using deep learning
- Making predictions using linear regression, polynomial regression, and multivariate regression
- Learn Data Visualization with MatPlotLib and Seaborn
- Implementing machine learning with Apache Spark’s MLLib
- Understanding reinforcement learning and building a Pac-Man bot
- Classify data using different algorithms like K Means clustering, Support Vector Machines, KNN, Decision Trees, Naive Bayes, and PCA
- Using train/test and K Fold cross validation
- Building a movie recommender system using item based and user based filtering
- Cleaning and evaluating your input data

**3. Machine Learning and AI: Support Vector Machines in Python**

Support Vector Machine is one of the most popular and powerful machine learning models around. In this Udemy course, you will learn everything about Support Vector Machines and how they are alike neural networks by working on practice questions and some real time projects like Image recognition, Spam detection, Medical diagnosis, Regression analysis, etc.

**What You will learn:**

- SVM practical applications such as image recognition, spam detection, medical diagnosis, and regression analysis
- Understanding the theory behind SVMs from scratch (basic geometry)
- Using Lagrangian Duality to derive the Kernel SVM
- Understanding how Quadratic Programming is applied to SVM
- Support Vector Regression
- Polynomial Kernel, Gaussian Kernel, and Sigmoid Kernel
- Building your own RBF Network and other Neural Networks based on SVM

**4. Data Science and Machine Learning Bootcamp with R**

This Udemy course one of the most comprehensive courses designed for both complete beginners with no programming skills and the experienced one waiting for a bigger jump in their career. You will start by learning basic programming in R and with move future with Data Science operations like data analysis, data visualization, data manipulation, etc. and using different Machine Learning algorithms with R.

**What You will learn:**

- Basic Programming in R
- Using R for Data Analysis
- Create Data Visualizations
- Using R to handle csv, excel, SQL files, etc.
- Web scraping using R
- Using R to manipulate data easily
- Using R for Machine Learning Algorithms
- Using R for Data Science

**5. A-Z Machine Learning using Azure Machine Learning (Azure ML)**

This Udemy course of Machine Learning using Azure Machine Learning, you will learn to build and deploy machine learning models. You will go through every concept in depth. This course teaches you basic and advanced techniques of Data processing, Feature Selection, and Parameter Tuning. Armed with these techniques, you will be able to match the results of an experienced data scientist.

**What You will learn:**

- Learn Making Data Science and Machine Learning Models using Azure ML.
- Understanding the concepts of Machine Learning algorithms
- Building Machine Learning models
- Choose the correct Machine Learning Algorithms
- Deploy different production grade Machine Learning algorithms

**6. Machine Learning Classification Bootcamp in Python**

This Udemy course is the perfect choice for those enthusiasts wanting to enhance their machine learning skills. This course provides students with the knowledge, hands-on experience of machine learning classification techniques such as Logistic Regression, Decision Trees, Random Forest, Naive Bayes, and Support Vector Machines (SVM). You are going to build 10 real world projects from scratch using various datasets.

**What You will learn:**

- Learn applying different advanced machine learning models to perform certain tasks like sentiment analysis and classify customer reviews
- Understand the theory and intuition behind several machine learning algorithms like K-Nearest Neighbors, Support Vector Machines (SVM), Decision Trees, Random Forest, Naive Bayes, and Logistic Regression
- Implement classification algorithms in Scikit Learn for K- Nearest Neighbors, Support Vector Machines (SVM), Decision Trees, Random Forest, Naive Bayes, and Logistic Regression
- Building an e-mail spam classifier using Naive Bayes classification
- Applying machine learning models to Healthcare applications
- Developing Models to predict customer behavior]
- Classifying data using K- Nearest Neighbors, Support Vector Machines (SVM), Decision Trees, Random Forest, Naive Bayes, and Logistic Regression
- Master Python Seaborn library for statistical plots
- Performing feature engineering and clean your training and testing data
- Python and Scikit Learn for Data Science and Machine Learning and Matplotlib library for data Plotting

**7. Introduction to Machine Learning for Data Science**

This Udemy course will help you understand what is computer science, data structures and algorithms, and data science. It will help you understand the impact of Machine Learning and Data Science on daily computation life is. It will help you build projects through regular practices on some of the actual IT problems faced nowadays.

**What You will learn:**

- Understand the different concepts of Computer Science, Algorithms, Programming, Data Analytics, Big Data, Artificial Intelligence, Machine Learning, and Data Science.
- Impacts of Machine Learning and Data Science
- What all sort of problems can be solved using Machine Learning
- how the Machine Learning Process works.
- Successfully implementing Machine Learning

**8. Machine Learning in JavaScript with TensorFlow js**

Want to use Machine Learning in JavaScript applications and websites, then this Udemy course is the one made for you. Machine Learning with TensorFlow.js provides you with all the benefits of TensorFlow, without the need of using Python. It does not just cover the basics, but by the end of the course, you will have advanced machine learning knowledge that you can use for your career enhancement. This Udemy course will guide you through complex topics in a practical way, and reinforce learning with in-depth real time projects.

**What You will learn:**

- Machine Learning with Javascript and TensorFlow JS 2.0
- Deep Learning and Neural Network concepts
- Why TensorFlow for JavaScript is a game changer
- Defining machine learning models
- Training machine learning models
- Data preparation for machine learning
- How to make accurate predictions
- Linear regression
- Binary classification
- Multi-class classification
- Heatmap visualization
- Scatter-plot visualization
- Importing and normalizing data
- Javascript and machine learning integration
- Shuffling, and splitting data
- In-depth labs for practical development

**9. The Complete Machine Learning Course with Python**

This Udemy course is for anyone willing and interested to learn machine learning algorithms with Python. In this course, you’ll go from beginner to extremely high level concepts of building different types of algorithms. By the end of the course, you will have trained machine learning algorithms to classify solutions for different problems.

**What You will learn:**

- Solve any problem with different powerful Machine Learning models
- Train machine learning algorithms to predict house prices, identify handwriting, detect cancer cells and more
- Learn Python, Seaborn, Matplotlib, Scikit Learn, Support Vector Machine, unsupervised Machine Learning etc

**10. Complete Machine Learning with R Studio – ML for 2020**

This Udemy course will help you to understand the bits and bytes of complete machine learning, algorithms, logic building, development, and how to deploy the same. Along with this, you will learn R programming to implement machine learning algorithms using R Studio. It includes different practice exercises and quizzes to assess your learning and offer a better understanding to all the topics.

**What You will learn:**

- Learn how to solve real life problem using the Machine learning techniques
- Machine Learning models such as Linear Regression, Logistic Regression, KNN etc.
- Advanced Machine Learning models such as Decision trees, XGBoost, Random Forest, SVM, etc.
- Understanding of basics of statistics and concepts of Machine Learning
- How to do basic statistical operations and run Machine Learning models in R

### Future Thoughts

Machine Learning is changing very rapidly. It was initiated by the pattern recognition methods and now have different large communities of developer contributing from all around the globe. It runs parallel with the concepts of Data Science and Deep Learning making it a required skill set for a candidate if they want to contribute in any of these fields. It offers a large learning and development scope on different platforms with different programming languages.

Udemy has been offering a very diversified machine learning set of options to learn from. Every course on Udemy is one of its kind covering different topics and practices. It is your will that you want to learn from all the options available.

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