Machine Learning Training in Vizag
Softenant Technoloiges is one of the best insitute for Machine Learning Training in Vizag. Mahchine learning is one of the best course for future. It is one of the subfield of Artificial Intelligence. This course covers super vised, unsupervised, refinforcement learning, regression techniques and clustering techniques. After completion of this course students will get complete knowledge on Machine Learning.
Who should take Machine Learning Course Training in Vizag at Softenant?
- Freshers having good logical and analytical skills.
- Professionals already having work experience on any domain.
- Students having Mathematical Skills and Mangement skills.
- Business analysts, Business Intelligence persons and Software Programmers.
Benefits of Machine Learning Training in Visakhapatnam
Why do I need this course?
This course is designed to teach you how to apply MLR in your own work. You can now take what you've learned about linear regression from my 'Linear Regression' course and start applying it to real-world problems!
How does this course help me out?
By completing this course, you'll learn how to build accurate predictions using MLR. Additionally, you'll have a better understanding of the concepts behind regression analysis, making sure that you're able to successfully model any relationship between two variables. Finally, you'll understand the importance of having sufficient sample sizes when working with regression methods.
- In general, it is a process of making any computer system understand to make accurate predictions through a given set of data.
- These predictions can be of any type from picking out the right fruit from the basket to observing people on the road in front of a self-driving car.
- Machine Learning is also involved in finding the correct word in the sentence to decide an email and put it in the spam folder.
- It can also recognize speech and generate captions for the YouTube video.
The main difference between Machine Learning and the traditional computer is, the developer doesn’t need to write any code for ordering the system to make the correct predictions.
Rather, a machine learning model knows itself to find the difference between all the predictions through a large amount of data fed in it. It is the data only which makes machine learning in predicting the right answer.
Machine learning Course in Vizag Syllabus
- What is Machine Learning
- History of Machine Learning
- Life cycle of Machine Learning
- How to Install Anaconda
- How to Get Datasets
- Data Preprocessing
- Types of Machine learning
- Supervised Machine Learning
- Unsupervised Machine Learning
- Reinforcement Machine learning
- Supervised vs Unsupervised Learning
- Regression Analysis
- Linear Regression
- Simple Linear Regression
- Multiple Linear Regression
- Polynomial Regression
- What is Classification
- Classification vs Regression
- Classification Algorithm
- Logistic Regression
- K-NN Algorithm
- Support Vector Machine Algorithm
- Naïve Bayes Classifier
- Linear Regression vs Logistic Regression
- Decision Tree Classification Algorithm
- Random Forest Algorithm
- Clustering in Machine Learning
- Hierarchical Clustering in Machine Learning
- K-Means Clustering Algorithm
- Apriori Algorithm in Machine Learning
- Confusion Matrix
- Machine Learning vs Deep Learning
- Dimensionality Reduction Technique
- Overfitting & Underfitting
- Principal Component Analysis
- What is P-Value
- Regularization in Machine Learning
- Examples of Machine Learning
- Semi-Supervised Learning
- Essential Mathematics for Machine Learning
- Overfitting in Machine Learning
- Types of Encoding Techniques
- Feature Selection Techniques in Machine Learning
- Bias and Variance in Machine Learning
- Machine Learning Tools
- Gradient Descent in Machine Learning
- Precision and Recall in Machine Learning
- Genetic Algorithm in Machine Learning
- Normalization in Machine LearningAdversarial Machine Learning
- Basic Concepts in Machine Learning
- Machine Learning Techniques
- Challenges of Machine Learning
- Model Parameter vs Hyperparameter
- Hyperparameters in Machine Learning
- Importance of Machine Learning
- Machine Learning and Cloud Computing
- Data Science Vs. Machine Learning Vs. Big Data
- Popular Machine Learning Platforms
- Deep learning vs. Machine learning vs. Artificial Intelligence
Difference between Artificial Intelligence and Machine Learning Course
- Although Machine Learning has gained a lot of success and theories, it far steps behind in achieving the level of Artificial Intelligence.
- In 1950, the birth year of Artificial Intelligence, it was defined as the machine having the ability to perform any task a human mind can do.
- These systems are capable of performing some of the following functionalities like planning, reasoning, problem-solving, perception, social intelligence, etc.
- On the other hand, Machine Learning involves various techniques and ways used in building Artificial Intelligence systems. It includes all the evolutionary computations needed for the system to undergo various mutations and combinations to give the perfect output.
- The computers are programmed in such a way that they are capable of copying the exact behavior of the human, irrespective of any domain. The best example of this is an autopilot system in a flying plane.
Why is Machine Learning So Successful?
The use of machine learning is not a new approach, but the interest in this area has boosted very much in recent years. The reason for the revival of machine learning is the deep learning that has set its records in the areas of speech and language recognition.
There are mainly two factors that led to this enormous growth of machine learning.
- The first one is the huge quantity of images, speech, videos, and texts through which the machine learning systems can be trained highly.
- And the second and more important factor is the vast amounts of parallel processing power systems.
- They are equipped with modern graphics processing units (GPUs) and if linked together into clusters, they are capable of forming machine learning powerhouses.
Today, with an internet connection, anyone can easily use these clusters to train these models through services provided by big companies like Amazon, Google, and Microsoft.
- The use of Machine Learning has boosted exponentially, therefore, most of the companies are now designing specialized hardware adaptable to train various machine learning models.
- An example of this can be taken as the custom chips like Google’s Tensor Processor Unit (TPU).
- These are the latest version chips that can increase the rate of machine learning models and their libraries through which they are trained.
These chips are not limited to train only Google DeepMind or Google Brain but also have a powerful impact on Google Translate and image recognition in Google Photos. It also helps in the services that allow users to build machine learning models with Google’s TensorFlow Research Cloud. However, after the launching of the second generation of these chips at Google’s I/O conference, they became more capable and advanced with the new TPUs.
Where is Machine Learning Used?
- Machine Learning is used everywhere around us and is the basic element of the modern internet. It is used to recommend the product you want to buy from Amazon or suggest a video to be watched on NetFlix.
- Even all the search engines including Google use machine learning algorithms to personalize your search experience for obtaining better results.
- The virtual assistants like Apple’s Siri, Amazon’s Alexa, the Google Assistant, and Microsoft Cortana, are all built using machine learning algorithms to optimize your queries.
- There is no limit to the advantages of machine learning in the modern era.
Therefore, Machine Learning is an extremely vast field. I believe, through this article, you must have got a brief understanding of Machine Learning. Further, to learn more you can enroll in the Best Machine Learning Training in Vizag.
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