Machine Learning Training in California

SynergisticIT, a leading Machine Learning Bootcamp can help you gain expertise in this emerging field. Our team of industry experts provides job-oriented training that help students prepare for their next professional move. This training is curated to give hands-on practice of how to apply ML algorithms, tools, & libraries for solving real-world problems in various industries.

With our Machine Learning training you get an opportunity to harness the potential of this emerging field and acquire the necessary skills for becoming a Machine Learning Engineer. It helps you explore the fundamentals of Machine Learning along with its advanced approaches. You will not only learn about theoretical underpinnings of Machine Learning, but also gain the practical knowledge needed for quickly applying these techniques to new problems.

Advantages of Machine Learning

Machine learning is the study of computer algorithms that let computers make predictions and decisions without being explicitly programmed. Machine Learning has become so pervasive that you probably use it hundreds of times a day without even knowing it. As we predominantly dependent upon gadgets and machines, it isn’t wrong saying that we are living in the Machine Learning Era.

At SynergisticIT you get the best Machine Learning Training in Bay Area. Our seasoned trainers teach the most innovative practices pertaining to ML & AI. Have a look at the reasons to enroll in Machine Learning:

The overall market share of Machine Learning is expected to reach around $8.81 Billion by 2022. This indicates about the rise in adoption of Machine Learning among companies.

By the end of this year, the demand for Machine Learning Engineers is expected to grow by 60%.

The growth rate for Machine Learning jobs is about 350% which is expected to create 2.3 million new jobs.

Machine Learning is a lucrative field offering higher salaries. Indeed reported the average salary for a Machine Learning Engineer as $144813 per annum in the US.

Over the years, the demand for Machine Learning Engineers has also surpassed the need for Data Scientists.

Despite the rapid growth in Machine Learning, there remains a skill shortage in this field. So, if you acquire the required skills and meet the demands of large companies, you will have a solid career in a technology that will continue to stay in-demand for the years to come.

Big Companies looking to hire Machine Learning Engineers

Overview of our Machine Learning Curriculum

We offer a structured curriculum providing beginners to advanced level training modules. It covers everything from Data Science, Python, Artificial Intelligence, to Business Analytics, Deep Learning and Computer Science. From our training students get to learn the practical application of ML. Have a look at our Machine Learning course content:

Beginner’s - Artificial Intelligence, Machine Learning and Business Analytics

  • Business Analytics & Business Intelligence
  • How to Work in the Cloud Practical Session
  • Machine Learning & Artificial Intelligence

Advanced - Artificial Intelligence and Machine Learning

  • Decision Tree and Random Forest Algorithm
  • Naïve Bayes and KNN Algorithm
  • Support Vector Machine Algorithm

Deep Learning and Computer Vision

  • Natural Language Processing (NLP) & Text Mining
  • Sentiment Analysis using Text Blob Practical Session and Task
  • Recommendation System Project Session and Task
  • Natural Language Processing using NLTK Practical Session and Task
  • Market Basket Analysis Session and Task

Python and Statistics for Data Science

  • Python Introduction and Practical Task
  • Numerical Python Practical Session and Task
  • Matplotlib Data Visualization
  • Pandas Data Analysis

Data Manipulation: Cleansing – Munging

  • Cleansing Data with Python
  • Filling missing values using lambda function and concept of Skewness.
  • Data Manipulation steps like sorting, filtering, merging, appending, derived variables, formatting, etc.

Data Analysis: Visualization Using Python

  • Introduction exploratory data analysis
  • Descriptive statistics, Frequency Tables and summarization
  • Univariate Analysis
  • Bivariate Analysis
  • Creating Graphs- Bar/pie/line chart/histogram/ boxplot/ scatter/ density)
  • Important Packages for Exploratory Analysis (NumPy Arrays, Matplotlib, seaborn, Pandas.

String Objects and Collection

  • String Object Basics and Methods
  • Splitting and joining strings
  • String Format Functions
  • List object Basics and Methods

Machine Learning-1

  • Introduction
  • Supervised, Unsupervised, Semi-supervised & Reinforcement
  • Train, Test & Validation splits
  • OverFitting & UnderFitting
  • Linear regression
  • R-square & adjusted R-square
  • Intro to Scikit learn
  • Training methodology
  • Hands on linear regression
  • Logistics regression
  • Precision Recall
  • Confusion matrix
  • ROC-Curve

Machine Learning-2

  • Decision tree
  • Cross validation
  • Bias vs variance
  • Ensemble approach
  • Bagging & boosting
  • Random forest
  • Variable importance

Machine Learning-3

  • XGBoost
  • Hyper parameter optimization
  • Random search cv
  • Grid search cv
  • Knearest neighbour
  • Lazy learners
  • Curse on dimensionality
  • KNN issues
  • Hierarchical Clustering
  • K-Means

Machine Learning-4

  • SVR
  • SVM
  • Naïve Bayes
  • Polynomial Regression
  • Ada Boost
  • Gradient Boost
  • Isolation Forest

Deep Learning

  • What is Deep Learning?
  • How do neural networks work?
  • Back propagation
  • ANN in python
  • What are convolutional neural networks?
  • Installing Tensor Flow & Keras
  • CNN in python
  • Activation function & Epoch

Natural Language Processing

  • NLP with Python
  • Sentiment analysis
  • Bags of words
  • Stemming
  • Tokenization

Tableau

  • Working with Tableau
  • Data organization
  • Creation of parameters
  • Advanced visualization
  • Dashboard data presentation

Model Deployment

  • Flask Introduction
  • Flask Application
  • Django end to end

Career Paths after taking Machine Learning Training in Bay Area

Being the most trusted ML training provider, we enlighten your knowledge of its core concepts. Once you acquaint with the best practices for applying ML algorithms, you will unlock a plethora of career paths in the leading industries such as Healthcare, Retail, Finance, Automotive. Also, you become qualified to apply for high-level positions like:

  • Machine Learning Engineer
  • Business Intelligence Developer
  • Data Scientist
  • Data Analysts
  • Algorithm Engineer
  • NLP Scientist
  • Research Engineer
  • Human-Centered Machine Learning Designer

Prerequisites for enrolling into the Best Machine Learning Training in California

Our Machine Learning training course does not require any prior knowledge or skills. However, for a better understanding of the concepts, we recommend students to meet the following prerequisites:

  • You should be comfortable with linear equations, data structures, calculus, variables, histograms, statistics, graph of functions, etc.
  • It is good to have some experience in programming/coding or be proficient in using programming languages like Python or Java.

Who is Eligible for this training?

The Machine Learning Training in Bay Area is designed for the people who want to build a robust career in Machine Learning, it is best-suited for:

  • Business Analysts
  • Information Architects
  • Analytics Managers
  • Undergraduates and graduates with an interest in Machine Learning
  • Developers seeking to step into Data Science
  • Professionals working in e-commerce or search engines

Get started with Machine Learning today, fast track your tech career. This training provides a complete overview of Machine Learning methodologies, to prepare you well for your next occupation as a Machine Learning Engineer. Our instructors allot project work as well as assignments to help you gain some real-world exposure in Machine Learning. Let’s meet your career goals. SynergisticIT- – The Best Programmers in the Bay area…Period!

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