Learn Machine Learning: 10 Projects In Finance & Health Care (12/2020)
Learn Machine Learning: 10 Projects In Finance & Health Care
WEBRip | English | MP4 | 1280 x 720 | AVC ~1038 Kbps | 30 fps
AAC | 128 Kbps | 48.0 KHz | 2 channels | Subs: English (.srt) | ~6.5 hours | 3.81 GB
AAC | 128 Kbps | 48.0 KHz | 2 channels | Subs: English (.srt) | ~6.5 hours | 3.81 GB
Genre: eLearning Video / IT & Software, IT Certification, Machine Learning
In this course you will build real world data science and machine learning projects of Healthcare industry with pythonWhat you'll learn
Building Classification Models
Building Regression Models
Working On Various Real World Machine Learning Problems
Building Machine Learning Models in Health care
Building Machine Learning Models in Finance
Requirements
Basics of Machine Learning
Healthcare & Finance knowledge is not required
Description
Machine Learning is no longer just a niche subfield of computer science but technology giants have been using it for years – Machine learning algorithms power Walmart product recommendations, surge pricing at Uber, fraud detection at top financial institutions, content that Twitter, LinkedIn, Facebook and Instagram display on social media feeds or Google Maps. Machine learning products are being used daily, perhaps without realizing it. The future of machine learning is already here, it’s just that the machine learning career is exploding now because of smart algorithms being used everywhere from email to mobile apps to marketing campaigns. If you are in search of the most in-demand and most-exciting career domains, gearing up yourself with machine learning skills is a good move now.
In this course, we are going to provide students with knowledge of key aspects of state-of-the-art machine learning techniques. We are going to build 10 projects of the Health Care & Finance industry from scratch using the real-world dataset, here’s a sample of the projects we will be working on:
Blood Donation Analysis
Mortality Prediction In ICU Using ANN
Kyphosis Disease Classification
Suicide Rate Trend Analysis
DNA Classification of Humans And Chimpanzee
NYSE Stock Price Prediction
RBI Resources Data Analysis
E-signing of a loan based on financial history
Prediction Of Default Of Credit Card
Hybrid Mutual Fund Analysis
Who this course is for:
Students who are curious in data science and machine learning
also You can find my other useful: Machine Learning-posts
General
Complete name : 5. Model building.mp4
Format : MPEG-4
Format profile : Base Media
Codec ID : isom (isom/iso2/avc1/mp41)
File size : 128 MiB
Duration : 15 min 12 s
Overall bit rate : 1 174 kb/s
Writing application : Lavf58.12.100
Video
ID : 1
Format : AVC
Format/Info : Advanced Video Codec
Format profile : Main@L3.1
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 : 15 min 12 s
Bit rate : 1 038 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) : 0.038
Stream size : 113 MiB (88%)
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 : 15 min 12 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 : 13.9 MiB (11%)
Default : Yes
Alternate group : 1
Complete name : 5. Model building.mp4
Format : MPEG-4
Format profile : Base Media
Codec ID : isom (isom/iso2/avc1/mp41)
File size : 128 MiB
Duration : 15 min 12 s
Overall bit rate : 1 174 kb/s
Writing application : Lavf58.12.100
Video
ID : 1
Format : AVC
Format/Info : Advanced Video Codec
Format profile : Main@L3.1
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 : 15 min 12 s
Bit rate : 1 038 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) : 0.038
Stream size : 113 MiB (88%)
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 : 15 min 12 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 : 13.9 MiB (11%)
Default : Yes
Alternate group : 1
Screenshots
Learn Machine Learning: 10 Projects In Finance & Health Care (12/2020)
Learn Machine Learning: 10 Projects In Finance & Health Care (12/2020)
Learn Machine Learning: 10 Projects In Finance & Health Care (12/2020)
Learn Machine Learning: 10 Projects In Finance & Health Care (12/2020)
Exclusive eLearning Videos ParRus-blog ← add to bookmarks
Learn Machine Learning: 10 Projects In Finance & Health Care (12/2020)
