
Complete Machine Learning and Data Science: Zero to Mastery
Genre: eLearning Video / Development, Data Science
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 Facebook 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
Requirements
A computer (Linux/Windows/Mac) with internet connection.
Two paths for those that know programming and those that don’t.
All tools used in this course are free for you to use.
Description
This is a brand new Machine Learning and Data Science course just launched January 2020 and updated this month with the latest trends and skills! Become a complete Data Scientist and Machine Learning engineer! Join a live online community of 270,000+ engineers and a course taught by industry experts that have actually worked for large companies in places like Silicon Valley and Toronto. Graduates of Andrei’s courses are now working at Google, Tesla, Amazon, Apple, IBM, JP Morgan, Facebook, + other top tech companies.
Learn Data Science and Machine Learning from scratch, get hired, and have fun along the way with the most modern, up-to-date Data Science course on Udemy (we use the latest version of Python, Tensorflow 2.0 and other libraries). This course is focused on efficiency: never spend time on confusing, out of date, incomplete Machine Learning tutorials anymore. We are pretty confident that this is the most comprehensive and modern course you will find on the subject anywhere (bold statement, we know).
This comprehensive and project based course will introduce you to all of the modern skills of a Data Scientist and along the way, we will build many real world projects to add to your portfolio. You will get access to all the code, workbooks and templates (Jupyter Notebooks) on Github, so that you can put them on your portfolio right away! We believe this course solves the biggest challenge to entering the Data Science and Machine Learning field: having all the necessary resources in one place and learning the latest trends and on the job skills that employers want.
The topics covered in this course are:
– Data Exploration and Visualizations
– Neural Networks and Deep Learning
– Model Evaluation and Analysis
– Python 3
– Tensorflow 2.0
– Numpy
– Scikit-Learn
– Data Science and Machine Learning Projects and Workflows
– Data Visualization in Python with MatPlotLib and Seaborn
– Transfer Learning
– Image recognition and classification
– Train/Test and cross validation
– Supervised Learning: Classification, Regression and Time Series
– Decision Trees and Random Forests
– Ensemble Learning
– Hyperparameter Tuning
– Using Pandas Data Frames to solve complex tasks
– Use Pandas to handle CSV Files
– Deep Learning / Neural Networks with TensorFlow 2.0 and Keras
– Using Kaggle and entering Machine Learning competitions
– How to present your findings and impress your boss
– How to clean and prepare your data for analysis
– K Nearest Neighbours
– Support Vector Machines
– Regression analysis (Linear Regression/Polynomial Regression)
– How Hadoop, Apache Spark, Kafka, and Apache Flink are used
– Setting up your environment with Conda, MiniConda, and Jupyter Notebooks
– Using GPUs with Google Colab
Whether you are new to programming, or want to level up your Data Science skills, or are coming from a different industry, this course is for you. This course is not about making you just code along without understanding the principles so that when you are done with the course you don’t know what to do other than watch another tutorial. No! This course will push you and challenge you to go from an absolute beginner with no Data Science experience, to someone that can go off, forget about Daniel and Andrei, and build their own Data Science and Machine learning workflows.
Machine Learning has applications in Business Marketing and Finance, Healthcare, Cybersecurity, Retail, Transportation and Logistics, Agriculture, Internet of Things, Gaming and Entertainment, Patient Diagnosis, Fraud Detection, Anomaly Detection in Manufacturing, Government, Academia/Research, Recommendation Systems and so much more. The skills learned in this course are going to give you a lot of options for your career.
Click “Enroll Now” and join others in our community to get a leg up in the industry, and learn Data Scientist and Machine Learning. We guarantee this is better than any bootcamp or online course out there on the topic. See you inside the course!
Taught By:
Andrei Neagoie is the instructor of the highest rated Development courses on Udemy as well as one of the fastest growing. His graduates have moved on to work for some of the biggest tech companies around the world like Apple, Google, Amazon, JP Morgan, IBM, UNIQLO etc. He has been working as a senior software developer in Silicon Valley and Toronto for many years, and is now taking all that he has learned, to teach programming skills and to help you discover the amazing career opportunities that being a developer allows in life.
Taking his experience in educational psychology and coding, Andrei’s courses will take you on an understanding of complex subjects that you never thought would be possible.
See you inside the course!
Who this course is for:
Anyone with zero experience (or beginner/junior) who wants to learn Machine Learning, Data Science and Python
You are a programmer that wants to extend their skills into Data Science and Machine Learning to make yourself more valuable
Anyone who wants to learn these topics from industry experts that don’t only teach, but have actually worked in the field
You’re looking for one single course to teach you about Machine learning and Data Science and get you caught up to speed with the industry
You want to learn the fundamentals and be able to truly understand the topics instead of just watching somebody code on your screen for hours without really “getting it”
You want to learn to use Deep learning and Neural Networks with your projects
You want to add value to your own business or company you work for, by using powerful Machine Learning tools.
also You can find my other helpful
(if old file-links don’t show activity, try copy-paste them to the address bar)
General
Complete name : 5. Display Offers + Extract Data.mp4
Format : MPEG-4
Format profile : Base Media
Codec ID : isom (isom/iso2/avc1/mp41)
File size : 130 MiB
Duration : 17 min 6 s
Overall bit rate : 1 065 kb/s
Writing application : Lavf58.12.100
Video
ID : 1
Format : AVC
Format/Info : Advanced Video Codec
Format profile : [email protected]
Format settings : CABAC / 4 Ref Frames
Format settings, CABAC : Yes
Format settings, RefFrames : 4 frames
Codec ID : avc1
Codec ID/Info : Advanced Video Coding
Duration : 17 min 6 s
Bit rate : 929 kb/s
Nominal bit rate : 3 000 kb/s
Width : 1 280 pixels
Height : 720 pixels
Display aspect ratio : 16:9
Frame rate mode : Constant
Frame rate : 30.000 FPS
Color space : YUV
Chroma subsampling : 4:2:0
Bit depth : 8 bits
Scan type : Progressive
Bits/(Pixel*Frame) : 0.034
Stream size : 114 MiB (87%)
Writing library : x264 core 148
Encoding settings : cabac=1 / ref=3 / deblock=1:0:0 / analyse=0x1:0x111 / me=umh / subme=6 / psy=1 / psy_rd=1.00:0.00 / mixed_ref=1 / me_range=16 / chroma_me=1 / trellis=1 / 8x8dct=0 / cqm=0 / deadzone=21,11 / fast_pskip=1 / chroma_qp_offset=-2 / threads=22 / lookahead_threads=3 / sliced_threads=0 / nr=0 / decimate=1 / interlaced=0 / bluray_compat=0 / constrained_intra=0 / bframes=3 / b_pyramid=2 / b_adapt=1 / b_bias=0 / direct=1 / weightb=1 / open_gop=0 / weightp=2 / keyint=60 / keyint_min=6 / scenecut=0 / intra_refresh=0 / rc_lookahead=60 / rc=cbr / mbtree=1 / bitrate=3000 / ratetol=1.0 / qcomp=0.60 / qpmin=0 / qpmax=69 / qpstep=4 / vbv_maxrate=3000 / vbv_bufsize=6000 / nal_hrd=none / filler=0 / ip_ratio=1.40 / aq=1:1.00
Audio
ID : 2
Format : AAC
Format/Info : Advanced Audio Codec
Format profile : LC
Codec ID : mp4a-40-2
Duration : 17 min 6 s
Bit rate mode : Constant
Bit rate : 128 kb/s
Channel(s) : 2 channels
Channel positions : Front: L R
Sampling rate : 48.0 kHz
Frame rate : 46.875 FPS (1024 SPF)
Compression mode : Lossy
Stream size : 15.7 MiB (12%)
Default : Yes
Alternate group : 1 Screenshots
✅ Exclusive eLearning Videos ← add to bookmarks
Feel free to contact me
when links are dead or want any repost
TurboBit
https://www.keeplinks.org/p27/67d3901a79858
RapidGator
https://www.keeplinks.org/p27/67d39853eaa1a
FileFactory