Hope Tutors offers the best Python with Machine Learning Course. We provide this course with the advanced course module. We design this course in such a way which fit the people who are willing to learn. Even they don’t have any prerequisite knowledge of machine learning.

We design this course for your successful carrier. We will teach you the fundamental skills of Machine Learning and Python Course. We will train you in new trends, Practices as well as in all aspects. Also, we will concentrate on training you with industrial expectation. The course covers all topics in exam point of view.

Hope Tutors provides the best Training in Chennai at affordable fees. We designed the course module as that you can learn effectively. We will make you master in the concepts of Python with Machine Learning.

Introduction to Machine Learning

Machine Learning is a type of Artificial Intelligence (AI). It will authorize software apps to be more exact in predicting outcomes. This is possible without programmed explicitly. Machine learning is a procedure for data analysis. It automates analytical model building which is a branch of AI. This idea is which computers should adapt to learn and gain experience. Machine Learning focuses on computer applications. This is to access data and use it by themselves.

Machine learning will allow the systems to learn automatically. It will allow working better from experience. ML algorithms simply focus on computer applications such as follows.

  • Detection of network intruders.
  • Email filtering.
  • Computer vision.

Computer Vision is inapt to develop an algorithm. This is for performing the task. It is related to computational statistics. This Statistics will focus on making a prediction using computers. For example, you post a photo. Soon you will give the suggestion as whom to tag in the photo. Nowadays ML Plays a major role in the IT field.

Why should you take Python with Machine Learning Course?

Python Training in Chennai

Machine learning is taking over the world. There is a growing need in the field for experts who will know the ins & outs of ML.

The machine learning market size is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022. With a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period.

Knowledge required for this course

You should have the following skill for this Python with Machine Learning course. They are,

  • You should have the fundamental knowledge of Python programming.
  • You should have a fair understanding of the basics of statistics & mathematics.

The skill you gain from this course:

After successfully completing our course, you will be a master’s in it. You will complete the course with the below skills.

  • Master in Supervised & Unsupervised learning concepts & Modeling.
  • Gain knowledge of the mathematics and aspects of machine learning.
  • Understand the operations of the following.
    1. Support vector machines.
    2. Linear regression.
    3. Decision tree.
    4. K-nearest neighbors.
    5. K means clustering.
  • Attain practical mastery over the Principles, algorithms & ML apps.
  • Graphical Models along with a solid foundation. This will be in Predictive Analytics & Statistics.

We provide complete course material. We will also provide the Classroom recorded videos for this course. It will coordinate all topics so you can easily understand the concepts. You can also refer the videos as well as material. We provide both offline and Online Classes. You can choose as per convenient of your own.

Who can take this course?

There is an increase in demand for skilled machine meaning engineers. We recommend this Python with Machine Learning course for the following persons. They are,

  • Developers
    • Those are aspiring to be a data scientist or machine learning engineer.
  • Analytics managers
    • Those are leading a team of analysts.
  • Business analysts
    • People want to understand data science techniques.
  • Information architects
    • People want to gain expertise in machine learning algorithms.
  • Analytics professionals
    • People want to work in machine learning or artificial intelligence.
  • Graduates
    • People to build a career in data science and machine learning.
  • Engineers.
  • Software and IT Professionals.
  • Data Professionals.

Minimum Eligibility for taking this course:

The candidate with a bachelor’s degree with a minimum of 1 year of work experience. The candidate with a degree in Mathematics or Statistics is also preferable.

Position suits you after this course:

Machine Learning Training in Chennai

Following are the positions which suit you after completing this course.

They are,

  • Business Analyst.
  • Product Analyst.
  • Machine Learning Engineer.
  • Data Scientist.

Real World Machine Learning Applications:

Machine learning plays a major role in today’s world. A pictorial representation of a few ML apps given below. We use this in our everyday lives.

  • Automatic Translation.
  • Traffic Prediction.
  • Web search and Recommendation Engines.
  • Online fraud detection.
  • Medical Diagnosis.
  • Text & Speech Recognition.
  • Email spam filtering.
  • Image Recognition.
  • Virtual Personal Assistants.

Machine Learning Training

 

Benefits of Machine Learning

  • Improves the precision over the technologies. This will use in the software industry and aid for the forecast of sales.
  • Machine learning is helpful in using artificial intelligence. AI, where the big volumes of data are used to train the machines with data.
  • The research & marketing division is in drastic need of people with ML knowledge.
  • Improves accuracy in the research areas. It prevents the business through anticipated loss.
  • Helps for detecting the spam & improves security to the data and business.

Future Scope of Machine Learning

Machine learning is still a complex demon. The husky form of ML Chennai is “deep learning”. This forms a mathematical structure called a neural network. The future of Machine learning is very bright. It is an incredibly powerful tool. Since ML can solve problems which we couldn’t solve.

Companies Using Machine Learning

Following are some top companies in the field. They are,

  • Amazon.
  • Facebook.
  • Google.
  • Apple.
  • Uber.
  • Ayasdi.
  • Digital Reasoning.
  • Darktrace.
  • Dataiku.
  • Feedzai.
  • IBM Watson.
  • Luminoso.
  • N-iX.
  • QBurst.
  • Qualcomm.
  • Skytree.
  • Instagram.
  • Industrial Light and Magic.
  • Spotify.
  • Quora.
  • Netflix.
  • Dropbox.
  • Reddit.
  • SurveyMonkey.

Salary Trends

You may get almost $110,129 as your average salary. Once you are done with this course, you will be the most preferring candidate. Most of the companies will show interest in hiring you.

This course will surely act as a block breaker in your carrier. Once you completed this course you may find the number of offers.

The bonus will be $9,892. The profit sharing will be $10,174. The salary details are shown below.

S: NO SPLIT – UPS PAY
1 Salary $75,629 – $149,105
2 Bonus $3,069 – $25,445
3 Profit Sharing $1,930 – $48,701
4 Total Pay $72,946 – $156,343

We hope you will understand how we train you in this course. Let your carrier start with our Hope Tutors. All the very best for your bright features. Be with hope and be with our Hope.

 

Python Interview Questions and Answers

Python Interview Questions and Answers

 

Python Interview Questions and Answers Part 2

 

Course Curriculum

Introduction to Machine Learning
Applications of Machine Learning Details 00:00:00
Supervised vs Unsupervised Learning Details 00:00:00
Python libraries suitable for Machine Learning Details 00:00:00
Regression
Linear Regression Details 00:00:00
Non-linear Regression Details 00:00:00
Model evaluation methods Details 00:00:00
Classification
K-Nearest Neighbour Details 00:00:00
Decision Trees Details 00:00:00
Logistic Regression Details 00:00:00
Support Vector Machines Details 00:00:00
Model Evaluation Details 00:00:00
Unsupervised Learning
K-Means Clustering Details 00:00:00
Hierarchical Clustering Details 00:00:00
Density-Based Clustering Details 00:00:00
Recommender Systems
Content-based recommender systems Details 00:00:00
Collaborative Filtering Details 00:00:00

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